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Hellenic Operational Research Society (HELORS)

http://eeee2013.epu.ntua.gr/

Book of Abstracts

26-28 September 2013Athens , Greece

UNDER THE AUSPICES OF THE

1963-2013

50th Anniversary

2nd International Symposium &

24th National Conference on Operational Research

Book of Abstracts

2nd

International Symposium & 24th

National Conference on Operational Research 1

Table of contents 1. Invited Speeches .................................................................................................... 6

2. Fullfilment Request Management (the approach) .............................................. 13

3. Reactive project scheduling in practice ............................................................... 14

4. A simple EOQ model with possible batch rejections ........................................... 15

5. Seismic Risk Assessment Using Mathematical Correlation and Regression ........ 16

6. Constructing Portfolios Using Argumentation Based Decision Making and

Performance Persistence of Mutual Funds ......................................................... 17

7. Project portfolio selection in a group decision making environment: Achieving

convergence with the Iterative Trichotomic Approach ....................................... 18

8. Mixed integer bilevel programming with upper level decision variables that

appear at the lower objective, but not in any of the lower level constraints ..... 19

9. A multi-periodic optimization modeling approach for the establishment of a

bike-sharing network: a case-study of the city of Athens ................................... 20

10. Optimizing long term fleet wide crew assignment .............................................. 21

11. Least Trimmed Absolute Deviation for Robust Location using Linear

Programming ....................................................................................................... 22

12. Bringing Europe and Third countries closer together through RES cooperation 23

13. Sharing expertise within Europe: The SEAP-PLUS method .................................. 24

14. Development of a Sustainable Energy Action Plan for the municipality of Chalkis

to support energy policy decision making in Greece ........................................... 25

15. Assessment and convergence of RES policy in EU member states ...................... 26

16. Assessing Energy and Environmental Policies for SMEs ...................................... 27

17. Combining performance and importance judgment in the MUSA method ........ 28

18. Evaluation of research activity in higher education: A Data Envelopment Analysis

approach .............................................................................................................. 29

19. Multi-Criteria Decision Network (MCDN) in Transportation ............................... 30

20. Regional Units Evaluation using Extended Fuzzy Analytic Hierarchy Process: The

case of Central Macedonia Region ...................................................................... 31

21. Measuring the efficiency of national innovation systems ................................... 32

22. Different formulations and Βenders decomposition on TSP ............................... 33

23. Telecommunications And A New Ways Of Works ............................................... 34

24. Improvements and comparison of non-Euclidean metrics in minisum problem 35

25. Scheduling with a due-window for acceptable lead-times.................................. 36

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26. Modelling a merge in network of warehouse facilities with two modes of

operation: cross docking and traditional warehousing ....................................... 37

27. Theory of attractive quality and multicriteria analysis: Analyzing customer

preferences on smartphone attributes ............................................................... 38

28. A hybrid fuzzy MCDM approach for evaluating financial performance of Iranian

companies ............................................................................................................ 39

29. Staff Attraction And Selection Methods: The Case Of Mobile

Telecommunications Companies In Greece ........................................................ 40

30. Techno-Economic Evaluation of Energy-Saving Measures in a Public Building ... 41

31. Development of a Multicriteria Decision Support System for selecting the most

advantageous route of the produced biogas in Landfills .................................... 42

32. Heterogeneous management information software for supporting energy-

related decision making problems ....................................................................... 43

33. Energy Consumption Evolution process .............................................................. 44

34. Agent based modelling and simulation for fuelwood consumption prediction .. 45

35. Designing A Practical Dynamic Lead-Time Quotation Policy In A Make-to-Stock

Queue................................................................................................................... 46

36. Performance analysis of power saving methods in wireless systems with

retransmissions: A queueing theory framework ................................................. 47

37. A batch constant retrial queue with multiple adaptive vacation policy .............. 48

38. Ordering policies for two products with demand substitution ........................... 49

39. Customer Equilibrium Policies in Observable Queues for Multiple Periods ....... 50

40. Evaluating new service development effectiveness in tourism: An ordinal

regression analysis approach ............................................................................... 51

41. A Decision Support System for Choosing Higher Education Studies ................... 52

42. A similarity metric for traces in Event Logs based on an outranking approach .. 53

43. Accounting information in the prediction of securities class actions .................. 54

44. Developing an ANP and Intuitionistic Fuzzy TOPSIS for Supplier Selection ......... 55

45. Evaluation of the operational performance of Greek public hospitals using a

robust multicriteria approach .............................................................................. 56

46. A stochastic location allocation model for primary health care network planning

............................................................................................................................. 57

47. The Obstetric Services in the Attica Area: Concentration Ratio and Competition

............................................................................................................................. 58

48. Medical errors in Greece: Main research findings through Greek courts’

judgments ............................................................................................................ 59

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49. Assessment of Policy Interrelationships and Impacts on Sustainability in Europe -

Empirical Analysis of the Energy & Climate Package ........................................... 60

50. Development of a knowledge platform on post Kyoto climate policy implications

............................................................................................................................. 62

51. A method for predicting electrical consumption in energy-intensive buildings

through energy performance indicators.............................................................. 64

52. Energy priorities’ identification for the municipality of Apokoronas for the

reduction of its carbon footprint ......................................................................... 65

53. Τhe Impact of Environmental Issues Upon Journalistically Mediated Nation

Images: An Intercultural Content Analysis........................................................... 66

54. A robust extension of the MUSA method based on desired properties of the

collective preference system ............................................................................... 68

55. Constructing robust efficient frontiers for portfolio selection under various

future returns scenarios ...................................................................................... 69

56. A DSS for Robustness Analysis in Stochastic UTA ................................................ 70

57. Using Robustness Analysis of Preference Models into Disaggregation -

Aggregation approaches for supporting interactivity .......................................... 71

58. Process Mining in software events of Open Source Software projects ............... 72

59. A Novel Formulation for the Integrated Quay Crane Assignment and Scheduling

Problem ................................................................................................................ 73

60. Generation of the exact Pareto set in multi-objective traveling salesman and set

covering problems ............................................................................................... 74

61. Are there low-risk trading opportunities in sport betting exchange markets? ... 75

62. Value focused pharmaceutical strategy determination with multicriteria decision

analysis techniques .............................................................................................. 76

63. Using process mining techniques for the analysis of the processes of an

emergency department in different periods of time .......................................... 77

64. MEDUTA: Integrating Simulation Modeling and Multiple Criteria Analysis To

Improve Emergency Department Performance .................................................. 78

65. Facilitating hospital department behavioral analysis using soft computing

techniques............................................................................................................ 79

66. The “Setting Up Young Farmers” measure and its environmental impacts on

rural areas ............................................................................................................ 80

67. The multiplicity of goals in tree-cultivating farms in Greece ............................... 81

68. From Data Envelopment Analysis to Multicriteria Decision Support: Application

to Agricultural Units Evaluation in Greece ........................................................... 82

69. Revenue Management of Perishable Products with Dual Sourcing and

Emergency Orders ............................................................................................... 83

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70. Use of Bi-Hyperbolic Activation Function to Optimize the Performance of

Artificial Neural Networks .................................................................................... 84

71. Personalized outdoor routing: Route planning techniques and algorithms ....... 85

72. Evolutionary Algorithms for Solving Resource Availability Optimization Problems

related to Client Service of Different Priority Classes .......................................... 86

73. Ant colony optimization in multi-project multi-mode resource constrained

project scheduling ................................................................................................ 87

74. Analysis of an integrated three-echelon supply chain with stochastic demand,

continuous review policies, lost sales and two-phase Coxian replenishment times

............................................................................................................................. 88

75. Centralized vs decentralized decomposition of supply chain using bi-level

schema ................................................................................................................. 89

76. Maximization of customer service level through variability reduction in Six Sigma

supply chains ........................................................................................................ 90

77. Modeling Supply Chain Processes: A Review and Critical Evaluation of Available

Reference Models ................................................................................................ 91

78. Supply chain optimization with regard to customer satisfaction: Solving with

GAMS and comparing with Analytic Hierarchy Process (AHP) ............................ 92

79. From “More than Moore” to “More Supply Chain”: Open Innovation Model and

Funnel Project Prioritization for Supply Chains with a focus on the

semiconductor industry ....................................................................................... 93

80. Public Transport Priority Strategies: Progress and Prospects.............................. 94

81. Environmental Vehicle Routing Problem ............................................................. 96

82. Use of SARIMA models to assess rail passenger flows: a case study of Serbian

Railways ............................................................................................................... 97

83. Overview of Non Linear Programming Methods Suitable for Calibration of Traffic

Flow Models ......................................................................................................... 98

84. Development of an objective function for the minimisation of Greenhouse Gas

(GHG) emissions from in port truck operations ................................................... 99

85. Simulation Analysis of a pilot handling system for the rail transport of

conventional semitrailers .................................................................................. 100

86. Towards a long-term security of supply in electricity markets: Testing capacity

mechanisms in an experimental setting ............................................................ 101

87. The Feasibility of Renewable Energy in the Gulf Cooperation Council Countries

........................................................................................................................... 102

88. Evaluating long term potential natural gas supply alternatives for Greece with

multicriteria decision analysis ............................................................................ 103

89. The effect of Wind Power penetration on the wholesale prices in Electricity

Markets .............................................................................................................. 104

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90. Methodology of Forecasting Natural Gas Demand in Greece ........................... 105

91. Optimization of medium-term natural and liquified gas supply for a Distribution

Company ............................................................................................................ 106

92. Public Data curation with the ENGAGE platform and OpenRefine ................... 107

93. Towards a Multicriteria Decision Support System for e-Government

Benchmarking in European Union ..................................................................... 108

94. A Methodology for Determining the Value Generation Mechanism and the

Improvement Priorities of Open Government Data Systems ............................ 109

95. An investigation of Open Data Infrastructures characteristics: rationale and end-

user perspective ................................................................................................. 110

96. Data.gov.gr Case Study ...................................................................................... 111

97. Dealing with Robustness in Government Decision-Making using Facilitated

Modelling ........................................................................................................... 112

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Invited Speeches 50th Anniversary of HELORS and its role within EURO Invited Speech by Sarah Fores General Manager and Professional Officer of the Association of European Operational Research Societies (EURO) Abstract As HELORS celebrates its 50th anniversary it is appropriate to reflect on its long history and its contributions on an international level. EURO, the Association of European Operational Research Societies, was formally constituted in 1976 in order to offer effective communication between established groups within Europe and to promote Operational Research using its strength as a regional subgroup of the International Federation of Operational Research Societies (IFORS). The Greek national OR society strongly supported EURO from the very beginning and, in 1975, the draft of the agreement for EURO was signed by the representatives of ten European OR Societies (Belgium, Denmark, Finland, Germany, Great Britain, Greece, Ireland, Netherlands, Sweden, Switzerland)'. In order to succeed in its aim to promote Operational Research within Europe EURO set up instruments such as a the European Journal of Operational Research, Working Groups, and Conferences. The success of EURO then depended on the enthusiasm and contribution of members within national OR societies, especially as funds were limited. Members of HELORS have actively participated in all EURO activities over the years and their research strengths have benefited the wider community through publications and collaborations. The society itself has actively contributed to strategic decisions and new initiatives within EURO by its representations on the EURO Council. Also Greece hosted the EURO-k conference in 2004. Despite various challenges EURO has continued to strive and develop as an Association thanks to the dedication of its member societies and individuals within them. It was with pleasure that EURO was able to reward the work of Professor Panos Pardalos with the highest distinction of the EURO Gold Medal at the most recent EURO-INFORMS conference and we wish to also acknowledge the contributions of all past and current HELORS members who have furthered the theory and practice of Operational Research. EURO would therefore like to wish HELORS a very happy birthday and we look forward to a very long and productive future.

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The Problem of Covering Solids by Spheres of Different Diameters Invited Speech by Nelson Maculan Full Professor of Optimization, Dept. of Systems Engineering and Computer Science, Graduate School of Engineering, COPPE, Federal University of Rio de Janeiro. President of the International Federation of Operational Research Societies (IFORS). Abstract We propose a mathematical programming formulation (Mixed-Integer Nonlinear Programming) for the problem of covering a solid by a finite number of spheres of different radii. We use this approach to model and study a complex sphere covering problem occurring in the configuration of a gamma ray machine radiotherapy equipment unit. We illustrate some results.

http://lsec.cc.ac.cn/~optim/CV-Prof.Maculan.pdf

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Optimization and Modeling in Energy Systems Invited Speech by Panos M. Pardalos Distinguished Professor at the University of Florida. Scientific Advisor of the LATNA Laboratory, Higher School of Economics, Moscow, Russia. 2013 EURO Gold Medal Winner at the EURO XXVI Conference Abstract Energy systems are undeniably considered as one of the most important infrastructures in the world. Energy plays a dominant role in the economy and security of each country. In this lecture, we are going to consider several difficult problems in energy networks, such as hydro-thermal scheduling modeling, electricity network expansion, liquefied natural gas and blackout detection in the smart grid.

http://www.ise.ufl.edu/pardalos/

http://eeee2013.epu.ntua.gr/InvitedSpeakers.aspx

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How the European Journal of Operational Research (EJOR) reflects the evolution of Operational Research? Invited Speech by Roman Slowinski Professor and Founding Head of the Laboratory of Intelligent Decision Support Systems within the Institute of Computing Science, Poznao University of Technology, Poland. Coordinating Editor of the European Journal of Operational Research (EJOR). Abstract The editor of EJOR will answer the question posed in the title, giving some characteristics of the journal, and explaining the approach of its editors to evaluation and selection of articles. Topics of Operational Research which recently raised the highest interest will also be pointed out. Some quantitative measures of the journal quality will be presented, along with the EJOR-R-index that has been proposed and used by the editors of EJOR to award 25 best reviewers each year. The last part of the presentation will be devoted to some advices addressed to young researchers on how to write articles about Operational Research.

http://idss.cs.put.poznan.pl/site/rslowinski.html

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What is a Decision Problem? Invited Speech by Alexis Tsoukiàs CNRS (Centre National de laRechercheScientifique) research director at LAMSADE, Université Paris Dauphine. Former President of the Association of European OR Societies (EURO). Abstract The talk introduces a general framework through which the whole potential set of decision problems can be described. The aim of the framework is to show that only a finite number of primitive characteristics describe a decision problem, thus reducing it to a finite number of combinations. In the talk we present in some details some of these characteristics, particularly emphasising the problem statement dimension. We also provide a number of simple examples in order to show how this framework helps in categorising current decision problems, in reformulating decision problems and in constructing formal arguments for the decision aiding process.

http://www.lamsade.dauphine.fr/~tsoukias/

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Steven Vajda, pioneer of OR Invited Speech by Jakob Krarup Professor Emeritus, D.Sc. & h.c.

Abstract Steven Vajda (1901-1995) was a mathematician, educator, one of mathematical pro-gramming’s true pioneers, and the person who introduced LP to both Europe and Asia. Upon having retired three times he was invited by Sussex University in 1973 to become Visiting Professor of Mathematics, in which role he continued actively, teaching and writing research papers for about 22 years, probably a record unsurpassed in the U.K. and anywhere. The influence of Steven on my carrier as an operational researcher can hardly be overrated. Mentor, co-author, and friend: I am greatly indebted to him.

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Health services in the middle of the crisis: An un-ended battle Invited Speech by N. Polyzos Ex-Secretary General (SG) of Ministry of Health (MoH), Associate Professor of Health Service Management, Democritus University of Thrace, ex Secretary General (SG) of Ministry of Health (MoH) Keywords: Health Care System in Greece, Health Policy, Organization, Coordination, Cooperation Abstract Introduction: At the end of 2009, health services in Greece faced serious discrepancies, because of uncontrolled deficits, lack of planning especially in HR and procurement of NHS, the absence of evaluation criteria and data, as well as urgent public health problems (e.g. epidemic flue, intensive care units, etc.). Health Policy: Under these circumstances and the burden of economic crisis, the most urgent goals were to solve the public health problems, to guide the regional and local administration, to support the procurement system, to prepare controlling mechanisms, etc. This diagnosis led to an incremental planning and every day rules. Organization-Coordination-Cooperation: The organization and coordination of such important projects needs high level of cooperation and commitment. Minister’s and SG’s offices worked together with main services (directorates etc.) on a weekly and monthly basis. Reports were concentrated and examined before relevant meetings in order to follow the goals. Esy.net was the main data base followed hospitals’ and health centers’ activities. EOPYY was the next big step towards consolidation of funds and PHC development. Results: Total NHS expenditure was decreased 11% (2011 to 2009) while medicines and sanitary materials were reduced 38%. At the same time inpatients were increased over 10%. Thus, average cost per patient declined at 20%. Satisfaction surveys show 50% positive and 20% negative results (the medium 30% has to be examined). Roles and Obstacles: The roles of political leadership and beurocracy were strongly correlated, so cooperation was quite effective. However, obstacles were put by various professional and other bodies, because of the strict financial measures and mainly the reforms undertaken during this period. Conclusion-the way ahead: Health Care System in Greece suffered from various problems during last decades. Many changes had to be done in a small period of time recently, under the restriction of financial crisis. New vision and strategy needs to be shaped and communicated to the general society. Public policy and administration should be connected beyond tools known to the developed countries (strategic and operational planning, organization and coordination, meritocracy and evaluation of HR, control and feedback of any goal, etc.). This battle must be continued.

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Fullfilment Request Management (the approach) S. Gkoutzioupas*, G. Valiris Vaktrianis 37, Zografou Athens 15772 * email of corresponding author: [email protected] Keywords: middleware, Application mediation, soa, esb, bpm, OM, Order Fulfillment, Service Abstract In this paper we introduce the FRM (Fullfilment Request Management). According to the FRM in a BSS / OSS system we can use a common approach in order to handle 1. orders 2. events 3. processes So systems like ESB, Order Management, Business Process Management etc can be implemented under a common architecture and a common implementation. We assume that all are 'requests' and depending the system we want to implement the request can be an event, an order, a process etc. So either we have N systems we have 1 system that covers all the above (ESB, Order Management, BPM ect) With the FRM we can have advantages as: 1. adaptation 2. interoperabillity 3. reusability 4. fast implementation 5. easy reporting In this paper we introduce the main principles in order to implement an FRM System.

mailto:[email protected]

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Reactive project scheduling in practice I. Petrides, E. Rokou*, K. Kirytopoulos Heroon Politechniou 9, Zografou, Greece * email of corresponding author: [email protected] Keywords: project scheduling, reactive, multi mode, evolutionary algorithms Abstract The vast majority of the research efforts in project scheduling over the past several years has concentrated on the development of exact and suboptimal procedures for the generation of a baseline schedule assuming complete information and a deterministic environment (Herroelen and Leus, 2004). In practice, during execution projects are often subject of considerable uncertainty, which may lead to numerous minor or major schedule disruptions. In project scheduling, uncertainty can take many different forms. Activity duration estimates may be off, resources may break down, work may be interrupted due to weather delay, new unanticipated activities may be identified, etc. All of these types of uncertainty may result in the infeasibility of the project baseline schedule. In general, project management wants to avoid these schedule breakages. This can be achieved by generating a baseline schedule in a proactive way, trying to anticipate certain types of disruptions so as to minimize their effect if they occur. If the schedule would still break down despite these proactive planning efforts, a reactive scheduling policy will be needed to repair the infeasible schedule (Deblaere et al, 2011). The objective of this paper is to propose a reactive scheduling procedure that may be used to revise or re-optimize a previously developed baseline schedule when unexpected events occur. More precisely, given a baseline scheduling that has been followed and updated with actual data from the project manager in a timely fashion, we assume that at a specific point of time, one or more disruptions on the schedule have been noticed or even forecasted due to new data and/or changes of one or more environmental variables, for example a material shortage is expected due to upcoming strikes. In this case the developed baseline schedule becomes infeasible during project execution due to the occurrence of one or more resource or activity disruptions. Therefore, we need a reactive policy that dictates how to revert to a feasible schedule that deviates as little as possible from the original baseline and resolves the schedule infeasibilities caused by the disturbances that occurred during schedule execution. This paper describes a new heuristic reactive project scheduling procedures that may be used to repair multi –mode resource-constrained project baseline schedules with variable resource availabilities and requirements that suffer from multiple activity duration and/or resource disruptions during project execution. The objective is to minimize the deviations between the baseline schedule and the schedule that is actually realized. The proposed approach is based on a combination of a genetic algorithm with simulated annealing and particle swarm optimization that aims at providing quick response and multiple solution scenarios to the project manager as to efficiently handle the experienced or forecasted disruptions. Finally, we discuss the computational results obtained by applying the proposed approach on a set of randomly generated project instances and on an illustrative example based on an actual construction project.


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A simple EOQ model with possible batch rejections K. Skouri*, I. Konstantaras, A.G. Lagodimos, S. Papachristos Department of Mathematics, University of Ioannina, 45110, Ioannina, Greece; Department of Business Administration, Business Excellence Laboratory, University of Macedonia, 156 Egnatia Street, 54006 Thessaloniki, Greece; Department of Business Administration, University of Piraeus,185 34, Piraeus, Greece; Hellenic Open University, Parodos Aristotelous 18, 26 335, Patra, Greece * email of corresponding author: [email protected] Keywords: Inventory; EOQ; Supply disruptions; Imperfect quality; Shortages Abstract We consider a simple EOQ setting with imperfect supply quality. In the literature, the simplest and most frequently used control policy to account for imperfect quality is to suppose that a fraction, say P, of goods received do not conform to quality standards. So, the parameter P is assumed to be either deterministic (fixed) or a random variable. In the later case, the form of the probability distribution function of P can be known, known but dependent from other unknown parameters, or unknown. This modelling for defectives items is known in the literature as the proportional yield (or imperfect quality) problem. In this paper, we study an alternative control policy calling for “all or none” decisions. Such a policy is usually deployed for non-itemized supplies (such as liquids, flours or grains) supplies, where the entire batch either conforms to specifications (so it is accepted) or does not conform (so it is rejected). Interesting, the proposed model can be considered as a special case of the random yield model, where the yield variable representing the fraction of defectives received takes the value 0 (the order, after inspection is not acceptable at all) or 1 (the order is fully acceptable). Under an “all or none” inspection policy which rejects all defective batches, we model system cost per unit time formally and we solve the respective optimization problem. The analysis shows that the global optimum can be obtained in closed-form, with expression being direct extensions to those of the classical EOQ (with backorders). In fact, if we assume perfect quality, these expressions degenerate to those of the latter problem. We also presented analytical results, showing that total cost per unit time is monotone increasing with increased supply quality as well as a systematic behaviour of both decision variables (i.e. the order quantity and the nominal maximum backorders level). Finally, numerical results highlighted the quantitative effects of imperfect supply quality, showing both total cost and decision variables particularly sensitive to variations of quality.


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Seismic Risk Assessment Using Mathematical Correlation and Regression C. Slave* Sos Erou Iancu Nicolae nr. 28, Voluntari, Jud Ilfov, Romania * email of corresponding author: [email protected] Keywords: correlation function, regression function, seismic risk, seismic force Abstract The actual design methods of structures under the influence of permanent, effective and climatic (wind, snow) loads, need an elastic behaviour of the structure and a static action of loads. The dynamic aspect of seismic action and inelastic behaviour of the structures affected by major earthquakes require specific design methods, governed by seismic design regulations. In Romania the field is covered by Seismic Design Code- part III –provision for seismic evaluation of Existing buildings, indicative P 100-3/2008. The article presents a calculation model of body A, building of Faculty of Land Reclamation and Environmental Engineering, Bucharest and also correlation and regression analysis of mathematical results to seismic evaluation of buildings, using MATHCAD PROFESSIONAL Software.


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Constructing Portfolios Using Argumentation Based Decision Making and Performance Persistence of Mutual Funds K. Pendaraki, N. I. Spanoudakis*

Applied Mathematics and Computers Laboratory, Technical University of Crete, University Campus, Kounoupidiana, 73100

* email of corresponding author: [email protected]

Keywords: Financial Decision making, Argumentation, Performance Persistence, Mutual Funds, Portfolio Management Abstract In this paper, an argumentation-based tool is proposed for the construction of mutual fund portfolios that outperformed the market index, based on the performance persistence of mutual funds. The sample data used in this study is provided from the Association of Greek Institutional Investors and consists of daily data of all domestic equity mutual funds (MFs) over the period 2000 to 2011. This empirical work from the field of finance uses argumentation-based decision making that provides a high level of adaptability in the decisions of the portfolio manager or investor, when his environment is changing and the characteristics of the funds are multidimensional, at the same time, taking into account his profile and preferences. Argumentation allows for combining such contexts and preferences in a way that can be optimized, thus, resulting in higher returns on the investment. Precisely, in our work we adopt the argumentation framework proposed by Kakas and Moraitis (2003), where the deliberation of a decision making process is captured through an argumentative evaluation of arguments and counter-arguments. A theory expressing the knowledge under which decisions are taken compares alternatives and arrives at a conclusion that reflects a certain policy. An analysis of the persistence of equity mutual funds is conducted, where a fund is defined to persist, if for consecutive time periods, it has returns above the median of the examined sample, relative to comparable funds. This study applies the “winner-winner, winner-loser” methodology, through the Z-test for repeat winners (Malkiel, 1995), the Odds Ratio Z-statistic (Brown and Goetzann, 1995) and the Chi-Square statistic (Khan and Rudd, 1995). For evaluating our results we defined scenarios for all years for which we had available data and for all combinations of contexts. That resulted to two investor types combined with the market status (growing or declining), plus two investor types combined with the high performance option, plus the market status combined with the high performance option, all together eight different scenarios, plus the simple contexts (5) and the general context (the sample data set provided 3,244 facts), run for eleven years each. After we confirmed our findings that there is statistically significant performance persistence for 1-year and 4-years holding periods, we applied portfolio funds participation strategies based on the persistence of mutual funds returns. Each one of the examined scenarios refers to different investment choices and leads to the selection of different number and combinations of MFs. A question we had to answer was if performance persistence of fund returns was economically significant, thus we validated the proposed methodological approach and the obtained portfolios through their comparison to the Athens Stock Exchange General Index return. Our empirical results in most of the cases outperform the general index of the target market and indicate that our tool is useful for successful mutual fund portfolios construction even though the examined period of the Greek market has been characterized by major fluctuations and certain financial crisis periods. To our knowledge, this study uses, for the first time, the combination of argumentation-based decision making for selecting the proper funds and the “winner-winner, winner-loser” methodology for composing efficient portfolios that outperform the market.


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Project portfolio selection in a group decision making environment: Achieving convergence with the Iterative Trichotomic Approach G. Mavrotas*, O. Pechak, D. Siatras, J. Psarras, E. Siskos Iroon Polytechniou 9, Zografos, Athens 15780 * email of corresponding author: [email protected] Keywords: Project portfolio selection, MCDA, Integer Programming, Group Decision Making Abstract Project portfolio selection is the problem of selecting a subset of projects from a wider set, optimizing one or more criteria and satisfying specific constraints. The basic tools are usually Multiple Criteria Decision Analysis and mathematical programming. In the presence of multiple decision makers the preferences are not unique and there must be a negotiation approach taking into account all the points of view. In the present work we use the Iterative Trichotomic Approach (ITA) in order to seek convergence. With ITA we can draw conclusions for the acceptance of each individual project as well as for the robustness of the final portfolio. The weights of evaluation criteria differ among the decision makers so that each one of them finally selects a different “optimal” portfolio. ITA can classify the projects into three sets: the green projects (selected in the “optimal” portfolio by all the decision makers), the red projects (not selected in the “optimal” portfolio by any of the decision makers) and the grey projects which are selected by some (but not all) the decision makers. A converging Delphi like process is designed for the weights so that in the next round new weights are calculated for every decision maker. The mathematical model is updated according to the new weights and solved. As the iterative process moves from round to round the green and the red set are enriched and the grey projects are reduced. The iterative process terminates when the calculated weights for all the decision makers provide the same “optimal” portfolio. The above method is illustrated with an example involving 133 energy projects. The final outcome is the final portfolio as compromise among the decision makers as well as the degree of accordance on each one of the projects that are finally selected. Finally a consensus index for the final portfolio can be extracted according to the progress of the converging process.


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Mixed integer bilevel programming with upper level decision variables that appear at the lower objective, but not in any of the lower level constraints E. Kostarelou*, G. Kozanidis Department of Mechanical Engineering, University of Thessaly, Leof. Athinon, Pedion Areos, Volos 38334, Greece * email of corresponding author: [email protected] Keywords: bilevel optimization, integer parametric programming, electricity markets, optimal bidding strategies Abstract We consider a class of mixed integer bilevel programs whose upper level decision variables appear at the objective of the lower level problem, but not in any of its constraints. Various optimization models exhibiting this structure are utilized to formulate the problem of devising the optimal bidding strategy of an electricity producer that participates in a day-ahead energy market. For this class of problems, we develop a heuristic solution algorithm first that utilizes important findings from the theory of integer parametric programming. The heuristic works by comparing all the distinct lower level optimal solutions that can be identified by varying parametrically a single upper level decision variable, while keeping all the other fixed. After the development of the heuristic, we illustrate how the proposed methodology can be modified to enable the generation of valid inequalities for suitable relaxations of the original problem, in which the so-called bilevel feasibility of the obtained solution is not guaranteed. We present two techniques for obtaining such relaxations. The first one is quite straightforward, calling for the suppression of the follower’s objective, while the second one transforms the original problem into a single level one, utilizing the lower problem’s KKT optimality conditions. Having as test case a bilevel programming application from the context of energy market optimization, we develop an exact cutting plane solution algorithm next that utilizes these valid inequalities. Our analysis considers two alternative schemes for the clearing of the market under investigation, a pay-as-bid scheme, according to which each producer is compensated with his corresponding offer for each MWh he provides to the system, and a uniform pricing scheme, according to which every producer is compensated at the same (marginal) price. We conclude with experimental results demonstrating the computational capabilities of the proposed solution algorithms, as well as their relative performance.


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A multi-periodic optimization modeling approach for the establishment of a bike-sharing network: a case-study of the city of Athens G.K.D. Saharidis*, A. Fragkogios, E. Zygouri

Department of Mechanical Engineering, School of Engineering, University of Thessaly, Leoforos Athinon, PedionAreos, 38834 Volos, Greece


Keywords: bike-sharing network, multi-periodic, optimization Abstract This study introduces a novel mathematical formulation that addresses the strategic design of a bicycle sharing network. Bike-sharing networks have received increasing attention during the last decades and especially in the 21st century. The bike-sharing network consists of these basic elements: the docking stations, the bicycles and the information technology (IT) interfaces, that have been recently introduced to improve the quality offered to the users. This paper specifically proposes a Pure Integer Linear Program that was solved using CPLEX for deciding the number, the location and the size of the bike stations that should be constructed and the suitable distribution of the required bicycle fleet among the stations. Given a set of candidate locations of bike stations and the time-dependent demand for bikes at these locations during a single day it is necessary to know where to place the bike stations and how many parking slots and bikes should each one have. The available budget of a city for the construction of the whole bike-sharing system is predefined and so are the costs of a single bike, a single parking slot and a single station. So it is a matter of optimization for the model to decide how many stations, bikes and parking slots it will include in its solution. The walking time between the locations is another parameter of the problem used to ensure the proximity of the constructed stations as far as this is possible. As regards demand in each location, it is split into “Demand for Pick-Ups” and “Demand for Drop-Offs”. The first one depicts how many users would like to take a bike from a station and the second one shows how many riders would like to leave a bike at a station. The demand is time-dependent. The 24 hours of the day are discretized into time intervals, during which different numbers of users come to a station either to pick up or to drop off a bicycle. The proposed approach is implemented on the 1st Municipal District of the Municipality of Athens. The demand patterns of a potential bike-sharing network in Athens are assumed to resemble the usage data of the bike-sharing network Velib’ of Paris. The authors of this paper chose 50 candidate locations where bike-sharing stations could be constructed. These 50 locations were categorized into the 4 clusters depending on their location, the cluster of “Housing” including candidate locations that are in densely populated areas, “Employment” which contains the locations close to business areas, “Subway” which includes the candidate locations where a metro station exists and “Spare Time” which contains the locations which are close to restaurants, coffee bars, shops etc. Furthermore, it is necessary to mention that the beginning of the day is considered to be 4am, when the solution of the model will show how many bicycles should be at each station in order to meet the day’s demand. Finally, the problem was solved for 2 cases with different values of parameters. More specifically, in the first case, the whole demand of a location where a station is not established is transferred to the closest established station while in the second case only 50% of the potential customers of these locations are willing to walk to the nearest allocated station and pick up or drop off a bike from it. The solution of the first case proposes a total number of 34 bike stations with 517 parking slots and 253 bikes. In the results of the second case the established stations are 40 with a total number of 461 parking slots and 210 bikes.


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Optimizing long term fleet wide crew assignment T. Varelas*, S. Archontaki, M. Livadioti 14 Akti Kondili, Piraeus 18545, Greece * email of corresponding author: [email protected] Keywords: crew assignment, binary integer programming, multi criteria analysis Abstract We present the unique long term maritime crew planning and assignment optimization that Danaos Corporation envisaged, Danaos Management has implemented and Danaos Shipping deployed as an enrichment of its ORISMA (Operation Research in Ship Management) toolkit. The major novelty in this system is the extension of the two coordinates, the number of vessels from one to whole fleet and the time horizon from couple of weeks to several months. Another initiative is the addition of a third dimension the teamwork index of the vessels’ management team. As assignment optimization problem the definition of an objective assignment function that should be optimized is required. We analyzed the problem and found out the formulas and the variables that are needed for the calculation of coefficients in the identified individual objectives that are combined in a weighted multi-objective assignment penalty function. The extension of coordinates and the team-working dimension increases the problem complexity and is hard to achieve optimal solution with conventional heuristics. So we combine operation research genetic and muliti-index axial integer models, efficient assignment algorithms and, new developed ones into one model adjusted to specific problem requirements. System also supports strategic decisions regarding the depth determination of the availability officers’ pool, the entries’ attributes such as rank, performance, availability and nationality avoiding in one hand unfeasible solutions and keeping on the other the safety pool level as less as possible. Furthermore an alert mechanism generates the appropriate triggers for actions whenever safety levels are reached and suggests mitigation plan. From design point of view the most important novelty of the ORISMA approach is the usage of ship officers’ quadruplet as the monitoring entity instead of the individual ship officer. ORISMA is awarded from INFORMS, the Institute of Operations Research and Management Science, the Franz Edelman finalist award for 2012.


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Least Trimmed Absolute Deviation for Robust Location using Linear Programming C. Chatzinakos*, G. Zioutas Aristotle University Thessaloniki, Faculty of Engineering, Greece * email of corresponding author: [email protected] Keywords: Mathematical programming, Robust Statistic, Outliers, Location Estimates Abstract Some robust location estimates μ are based on Least Absolute Deviations (LTAD). In this work we improve (reduce the bias) the LTAD estimates by trimming the deviations of the outliers. We develop the Least Trimmed Absolute Deviation (LTAD) estimator, where the deviations of the bad influential points (outliers) reduced to zero. Although, this is a combinatory problem and it is solved with mixed integer programming (MIP), we propose a new technique where the problem is solved with linear programming (LP). In the new LP formula the weight decisions variables wi , 0< wi<1, become zero-one by centralizing the data. In the new approach the LP formula is repeated several times in order to centralize to zero the data points. Therefore the combinatory problem (MIP) becomes LP problem and the solution is obtained significantly faster. Also, the new technique leads to better robust and efficient local estimates.


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Bringing Europe and Third countries closer together through RES cooperation BETTER Consortium, Presentation by Charikleia Karakosta 9 Heroon Polytechniou street, 15780, Athens, Greece * email of corresponding author: [email protected] Abstract The BETTER - Bringing Europe and Third countries closer together through renewable Energies intends to address RES cooperation between the EU and third countries in several dimensions. The starting point is given through the cooperation mechanisms provided by the RES Directive, allowing Member States to achieve their 2020 RES targets in a more cost efficient way, and thereby including the possibility to cooperate with third countries. Thus, the core objective of BETTER is to assess, through case studies, stakeholders involvement and integrated analysis, to what extent cooperation with third countries can help Europe achieve its RES targets in 2020 and beyond, trigger the deployment of RES electricity projects in third countries and create synergies and win-win circumstances for all involved parties. The case studies focusing on North Africa, the Western Balkans and Turkey will investigate in detail the technical, socio-economic and environmental aspects of RES cooperation. Complementary to these bottom-up analyses, an integrated assessment will be undertaken from the “EU plus third countries” perspective, including a detailed quantitative cost-benefit evaluation of feasible policy approaches, as well as strategic power system analyses. Moreover, co-effects such as impacts on the achievement of EU climate targets, energy security and macro-economic aspects will be analysed. The final outcome will be a fine-tailored policy package, offering a concise representation of key outcomes, guidelines for practical implementation of RES cooperation and actions plans reflecting regional specifics. For more information about BETTER you may visit the project website: www.better-project.net Key expected results from BETTER include the following: - Evaluation through case studies and integrated analysis of the impacts that the implementation of the cooperation mechanism in the studied countries can have in helping Europe achieve its RES targets as well as the associated co-effects (market opportunities, grid requirements, environmental and socio-economic impacts, etc.) for both Europe and third countries. - An action plan to foster renewable energy production, transfer and use in the EU member states, as well as third countries through cooperation initiatives highlighting its strengths, weaknesses opportunities and threats. - Policy recommendations with regards to: (i) the implementation of the RES cooperation mechanism for each case study region and for the European Union, (ii) the implementation of the joint project with third countries mechanism in general and (iii) the comparison of the third countries cooperation mechanism with the other EU internal RES cooperation mechanisms. - The establishment of a solid stakeholder network between Europe and selected third countries to foster RES cooperation and knowledge transfer. - Generation of knowledge and dissemination material and activities in order advocate in favour of EU RES cooperation mechanisms as well as RES deployment.


http://www.better-project.net/

http://www.better-project.net/

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Sharing expertise within Europe: The SEAP-PLUS method Ι. Skoula*, A. Stavrakaki*, H. Doukas** * EPTA SA, Environmental-Consultants Engineers - www.epta.gr ** National Technical University of Athens, School of Electrical and Computer Engineering, Decision Support Systems Lab 9, Iroon Polytechniou str., 15780, Zografou. * email of corresponding author: [email protected] Keywords: Sustainable Energy Action Plans, SEAP, sustainable energy, climate change policy, energy policy, Covenant of Mayors, local action, local authorities Abstract Covenant of Mayors (CoM) holds a pivotal role in achieving the targets of 20-20-20 by 2020 set by the EU Climate Action and Energy Package. Nevertheless, due to a number of barriers, municipalities in many countries are hesitant in adhering to the CoM or preparing and implementing the necessary Sustainable Energy Action Plan (SEAP). Barriers include amongst other, the lack of available funds, the lack of technical expertise and capacity in municipalities, the lack of accessible and reliable energy data and the lack of cooperation with energy providers and stakeholders, as well as the fact that respective regional stakeholders haven’t integrated CoM in their programmes, actions and regional policies. SEAP-PLUS aims to overcome these barriers, as well as support the CoM and enhance its results and impact in both quantitative and qualitative terms. The SEAP-PLUS methodology seeks to: bring more signatories and covenant supporters or coordinators in CoM and thus expand the CoM initiative within Europe; support CoM signatories in developing climate change and energy policies by preparing more and better SEAPs; triggering cooperation of local authorities with regional authorities and energy stakeholders in order to ensure that reliable energy data are used in energy planning; and also facilitate cooperation between experienced and learning CoM participants across European countries. Thirteen organizations from eleven European countries are currently following the SEAP-PLUS methodology developed. Six pairs of regional organizations have been created to facilitate direct transfer of knowledge and know-how from experienced organizations to learning ones. The whole SEAP preparation and implementation process is being assessed, in view of the specific country conditions. The process has already led to improvements in the development of SEAPs in learning organizations, but has also benefited experienced ones by helping them add new perspectives to current practices. In addition, collaboration with the respective energy stakeholders, for access to the best available localized energy data, is being cultivated through specific actions. At the same time, both experienced and learning partners provide technical support to participating municipalities in the eleven countries involved. Local authorities are also being mobilized to participate in a large number of events and activities across Europe, some of which took place during the 2013 Sustainable Week. Various dissemination activities ensure that practical results, best practices and new ideas reach and inspire key target groups, including local authorities, regional authorities and national or European decision makers related to the Covenant of Mayors.

http://www.epta.gr/


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Development of a Sustainable Energy Action Plan for the municipality of Chalkis to support energy policy decision making in Greece A. Papapostolou*, D. Angelopoulos, J. Psarras Decision Support System Lab, School of Electrical and Computer Engineering, National Technical University of Athens, Iroon Polytechneiou 9 Str., 157 73, Athens, Greece * email of corresponding author: [email protected] Keywords: Energy policy and planning, Sustainable development, Climate change mitigation, Energy efficiency. Abstract The Covenant of Mayors is a European Initiative, involving local and regional authorities. The signatories commit themselves voluntarily to improve the energy efficiency and reduce by at least 20% greenhouse gas emissions within the boundaries of the municipality by 2020. This can be achieved by the integration of Renewable Energy Sources (RES) and Rational Use of Energy (RUE) technologies. One year after the signing of the Covenant, the municipalities are called upon to submit a local council approved Sustainable Energy Action Plan (SEAP). The SEAP includes the municipality’s Baseline Emission Inventory and the Actions through which it intends to achieve the previous target. In the frame of the Covenant of Mayors, this paper aims at the development of a Draft Sustainable Energy Action Plan for the municipality of Chalkis, in Evia, Greece. Firstly, the energy consumption of all the fields was estimated by collecting the essential energy data and by applying estimations and inevitable approximate methods based on published studies, when necessary. Subsequently, the emission inventory was complied for the year 2011 in accordance with the principles and emissions factor database of Intergovermental Panel on Climate Change (IPCC). The methodology and procedure of the dissertation are following the guidelines that the Covenant of Mayors initiative is suggesting. Finally, possible RES and RUE actions were proposed, targeting to the improvement of the municipality’s energy efficiency and the completion of its CO2 reduction target. In moving towards this objective, local authorities will propose and implement RES and RUE technologies and policy measures. This would involve ambitious and pioneer measures in buildings, agriculture, fishing and transport. In addition, these actions were chosen after discussion with the local authorities and taking into account the general characteristics of the area, the existing infrastructures and the current grants which support the implementation of the proposed package of technologies and measures.


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Assessment and convergence of RES policy in EU member states DIA-CORE Consortium, Presentation by D. Angelopoulos 9 Heroon Polytechniou street, 15780, Athens, Greece * email of corresponding author: [email protected] Keywords: Renewables, Policy, investments, Dialogue, EU, 2020 Abstract With Directive 2009/28/EC the European Parliament and Council have laid the grounds for the policy framework for renewable energy sources (RES) until 2020. The aim of the “Policy Dialogue on the assessment and convergence of RES policy in EU Member States – DIA-CORE” project (http://www.diacore.eu), started in April 2013 and carried out under the Intelligent Energy – Europe programme, is to ensure a continuous assessment of the existing policy mechanisms and to establish a fruitful stakeholder dialogue on future policy needs for renewable electricity (RES-E), heating & cooling (RES-H), and transport (RES-T). Thus, DIA-CORE shall facilitate convergence in RES support across the EU and enhance investments, cooperation and coordination. This project shall complement the Commission’s monitoring activities of Member States (MSs) success in meeting 2020 RES targets and builds on the approaches developed and successfully applied in the previous IEE projects OPTRES, FUTURES-E and RE-Shaping. To facilitate decision-making, DIA-CORE offers detailed cross-country policy evaluations, presented in an interactive web-based RES policy assessment database. This policy assessment database will be linked to (and build on the information provided by) the RES-Legal database currently developed for DG ENER. Indicators on effectiveness and efficiency of existing policies for RES in all sectors will be extended and updated, complemented by an analysis of costs and benefits of RES on MS level. Future consequences of policy choices will be analysed in detail using the Green-X model, highlighting possible additional policy needs for 2020 target achievement and contributing to upcoming 2030-related discussions. In general, the optimisation of the design of the individual RES policies, namely feed-in tariffs, premiums, investment incentives etc in line with future policy needs is a key focus of the project. In the course of DIA-CORE, an intense and continuous stakeholder dialogue will be established based on a series of workshops and continuous involvement of national and European key decision makers. To ensure the use of the project findings and recommendations in future policy making, intensified experience exchange forms an overarching component of this project. Complementary to the comprehensive interactive web-based RES policy database, this exchange will be organised by way of workshops/conferences, online meetings, presentations at external events and through the use of social media.


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Assessing Energy and Environmental Policies for SMEs A. Tsiousi*, J. Psarras Heroon Polytechniou 9, 15780 Zografou, GREECE * email of corresponding author: [email protected] Keywords: Multi-criteria analysis, Linguistic variables, TOPSIS, Small Medium Enterprises, Sustainable Development Abstract The current financial and economic crisis, as well as the wider social and environmental pressures, put seriously into question the traditional development patterns. These pressures create high expectations for coordinated actions and holistic interventions towards a competitive economy, through the adoption of “green” practices. Several methodologies are used for the collection and organization of data for companies’ energy and environmental corporate responsibility. This fact creates immediately the question of how these data can be used more effectively, since analytic data and information do not constitute energy and environmental policy. Nowadays, it is imperative need for the State to support Small Medium Enterprises (SMEs) operation in this difficult business environment through the development and adoption of appropriate policies, fostering green entrepreneurship and green energy growth. Integrated approaches and methodologies for managing energy and environmental issues, as an aspect of CSR are a central challenge towards SD. This paper aims to present a coherent and transparent methodological multi-criteria framework, using linguistic variables, for assessing companies’ energy and environmental corporate policies. The use of linguistic variables is a realistic approach, taking into consideration that the information needed is often unquantifiable, imprecise and uncertain. The proposed framework is based on the developed 2-tuple TOPSIS method, with its application to a number of SMEs. Moreover, a comparison with the 2-tuple LOWA operator and a sensitivity analysis are provided. According to the results, SMEs that integrate systemic environmental practices and come from countries with essential implementation of Corporate Social Responsibility (CSR) concepts achieve high overall performance, while SMEs with lower performance have commitments and goals limited only to the required legislation. The results of the study can support the State in focusing its resources on those types of companies and applying the appropriate practices that ensure green entrepreneurship.


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Combining performance and importance judgment in the MUSA method Y. Politis* (1), E. Grigoroudis (2) (1) School of Science and Technology, Hellenic Open University Parodos Aristotelous 18, GR26 335, Patra, Greece, (2) School of Production Engineering and Management, Technical University of Crete * email of corresponding author: [email protected] Keywords: MUSA extension, robustness improvement Abstract The multicriteria method MUSA (MUlticriteria Satisfaction Analysis) is a preference disaggregation model following the principles of ordinal regression analysis (inference procedure). The method is used for measuring and analyzing customer satisfaction and aims at evaluating the satisfaction level of a set of individuals (customers, employees, etc.) based on their values and expressed preferences. This study presents an extension of the MUSA method based on additional customer preferences. In particular, a customer satisfaction survey may include, besides the usual performance questions, preferences about the importance of the criteria. Using such questions, customers are asked either to judge the importance of a satisfaction criterion using a predefined ordinal scale, or rank the set of satisfaction criteria according to their importance. All these performance and importance preferences are modeled using linear programming techniques in order to assess a set of marginal satisfaction functions in such a way that the global satisfaction criterion and the importance preferences become as consistent as possible with customer’s judgments. Based on these optimality criteria, the extension of the MUSA method is modeled as a Multiobjective Linear Programming (MOLP) problem. The main aim of the study is to show how combining customers’ performance and importance preferences, the robustness of the estimated results may be improved compared to the original MUSA method. An illustrative example is presented in order to show the applicability of this approach, while several MOLP techniques (e.g., heuristic method, compromise programming, global criterion approach) and post-optimality approaches are applied.


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Evaluation of research activity in higher education: A Data Envelopment Analysis approach Y. G. Smirlis*, D. Sotiros, D. K. Despotis, G. Koronakos Department of Informatics, University of Piraeus 80, Karaoli and Dimitriou, 18534 Piraeus, Greece * email of corresponding author: [email protected] Keywords: Data Envelopment Analysis (DEA); piece-wise linear Data Envelopment Analysis (PL-DEA); research activity; higher education Abstract Research is an important activity of the members of academic stuff in higher education. The extent and the quality of their research records determine their profile and play, or they should play a key role in their advancement. As the research activity of a University department is strictly determined by the research activity of its members, the quality of the individual research outcomes improve the recognition of the University department and affect its position in international academic rankings. In this paper we develop a Data Envelopment Analysis (DEA) assessment framework to evaluate the research activity of individual, members of academic stuff in comparable University departments. The selected factors (inputs and outputs) have a meaningful interpretation in the analysis and enable to perform the assessment by taking into account both the extent as well as the quality of the research records. The duration of the research activity, the funds received (in monetary values) and the teaching load (adjusted average) are defined as inputs. Outputs are the number of publications in journals ranked as A+ or A, the number of publications in journals ranked as B or C, the publications in unranked journals, publications in conferences, the number of research programs in which the researcher participates and the number of citations (excluding self-citations). The journal rankings are drawn from the Excellence in Research for Australia (ERA) 2010 journal classification system. The data are collected from Scopus, Google Scholar, university stuff records and CVs. To facilitate the incorporation of a quality aspect in our assessments, a piece-wise linear variant of the DEA model with assurance region constraints is employed. Assuming convex value functions for the publications in highly ranked journals and concave value functions for the publications in unranked journals, we reward the quality research records while diminishing the contribution of extensive publications in non-quality journals in the overall research performance. The proposed assessment approach is illustrated by using an anonymous data set.


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Multi-Criteria Decision Network (MCDN) in Transportation J. Trujillo*, C. Gonzalez Universidad Católica de Colombia; Av. Caracas 46-72, Bogotá, Colombia * email of corresponding author: [email protected] Keywords: supply chain management, Multi-Criteria Decision Making, Logistic Decision Units, Transportation, Multi-criteria Decision Network Abstract It introduces the concept of Multi-Criteria Decision Network (MCDN) for Transport Logistics Function (TLF), developed from the literature review and sets it as a tool to address the problem of decision units (DUs) supply and distribution channels for the selection of mode of transportation, shipping and freight consolidation degree with a outranking technique. This article is divided into three parts, the first identified quantitative criteria, qualitative and their interrelationship in Logistics Decision Units (LDU). In the second part, we identify and discriminate the alternatives. The third section sets out the methodology for using the MCDN and nomenclature in the TLF, and finally applies the proposed methodology to a case study of transportation of green coffee from Colombia to various destinations. It validates the use of variables in the state of the art through the methodology and the proposed technique.


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Regional Units Evaluation using Extended Fuzzy Analytic Hierarchy Process: The case of Central Macedonia Region G.K. Koulinas*, O.E. Demesouka, I. Sougkara, A.P Vavatsikos, K.P. Anagnostopoulos Dpt. of Production and Management Engineering, 12 Vas. Sofias st., 67100, Xanthi, Greece * email of corresponding author: [email protected] Keywords: Regional Planning, Central Macedonia, Multicriteria Analysis, Fuzzy AHP Abstract Multicriteria Analysis is one of the most important tools for the decision-making process and is applied in many areas such as economy, management, technology and social sectors. Multicriteria Analysis facilitates the representation of multidimensional problems and simplifies the decision-making process due to its flexibility. Given that it can be used to evaluate regional units in order to investigate inter/intra-regional inequalities. The paper at hand aims to provide such an evaluation aiming to provide guidelines regarding the planning of interventions and to highlight priorities in the spatial context. This is achieved using the most popular extension of Analytic Hierarchy Process (AHP) to fuzzy logic, which is known as Extended Fuzzy AHP. The case study is performed the Central Macedonia Region, which is divided into seven regional units; Thessaloniki, Serres, Imathia, Chalkidiki, Pella, Pieria and Kilkis. These units are evaluated using demographic, geographic, urban, social, environmental and economic data. Technically this is achieved using a four levels hierarchy. The first level represents the overall analysis goal, which is the evaluation of Central Macedonia regional units. The second level includes the four criteria, used to apply the evaluation. The criteria referring to the units are: the productivity, the social characteristics, the technical characteristics and the environmental and geographical characteristics. At the third level, the sub-criteria of the above criteria are set. Each criterion is analyzed into six sub-criteria. Finally, the seven units of the Central Macedonia Region are settled in the hierarchy’s fourth level. The proposed framework can be a useful tool for both policy makers and practitioners since it provides both the capabilities and requirements of the Region of Central Macedonia as whole as much as at a county level. In that sense it can be used to provide indicators that can be used by the investment programs operators of Greek public sector, as well as the operators and investors of private sector.


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Measuring the efficiency of national innovation systems Y. Goletsis*, E. Giannouli, E. G. Carayannis Dept of Economics, University of Ioannina, University Campus, 45110 Ioannina, Greece * email of corresponding author: [email protected] Keywords: National Innovation Systems, efficiency, Data Envelopment Analysis, two-stage network DEA Abstract Innovation is considered as a major factor providing competitive advantage to firms. As a result national innovation systems focus on the interaction between knowledge production and the embedded environment. Academia, private sector and government intervention are interlaced into a ‘triple helix’ system that can boost the competitiveness and sustainability of economies. Applying systemic thinking into the process, the concept of a national innovation system provides modelling of all these interdependencies. Measuring the performance of national innovation systems remains a high priority in the political agenda, especially amidst the economic crisis. Benchmarking, best practices and identification of weaknesses can become valuable tools in policy formulation. In this framework, in the current work we examine the evolution of the efficiency of national innovation systems over time using Data Envelopment Analysis (DEA). DEA can be used to enrich the rankings provided by the usually used statistical indicators. DEA can overlook the lack of a concrete production function and can accommodate multiple inputs and non-linearity. Different models are applied including super-efficiency, allowing for country ranking. Additionally, we apply a two-stage network model, so as to model the distinct but linked different innovation processes, i.e. knowledge production and knowledge commercialization. In this modelling, researchers, R&D expenditures and R&D stock are exploited for the production of knowledge and scientific outputs; these in turn, are commercialized and finally increase commercial outcomes. The above methodology is applied in 33 OECD countries; over a period of ten years. Efficient and non-efficient countries are identified. Results are discussed and compared. Country rankings differ when the two-stage network DEA is applied; this could be an indication that this modelling provides a more detailed insight of the innovation system.


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Different formulations and Βenders decomposition on TSP G. Kolomvos*, G. K. D. Saharidis, G. Liberopoulos Department of Mechanical Engineering, University of Thessaly, Leoforos Athinon, Pedion Areos, 38834 Volos, Greece * email of corresponding author: [email protected] Keywords: traveling salesman problem, benders decomposition Abstract We consider exact solution methods for the traveling salesman problem (TSP) and we examine different formulations. We particularly consider the conventional, the sequential, three time-staged and three flow-based formulations from (Dantzig, Fulkerson, & Johnson, 1954), (Miller, Tucker, & Zemlin, 1960), (Gavish & Graves, 1978), (Finke, Clauss, & Gunn, 1984), (Wong, 1980), (Fox, Gavish, & Graves, 1980) and (Vadja, 1961) respectively. In general, the TSP can be viewed as an assignment problem coupled with the different forms of subtour elimination constraints associated with each formulation. We distinguish the master problem which is the assignment problem augmented with the feasibility cuts added at every iteration. The worker problem essentially consists of the subtour elimination constraints that take different form according to the formulation. We apply the Benders decomposition on these formulations and observe their behaviour compared to the original formulations. We also compare results against progressive addition of subtour elimination constraints. We report the number of iterations and solution times on a TSP testbed which includes randomly generated instances as well as problems coming from the well-known TSPLIB. We report results on the comparison of the different formulations and the Benders decomposition approaches.


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Telecommunications And A New Ways Of Works K. Nikolaidis* Ikoniou 65 , 69100 Komotini * email of corresponding author: [email protected] Keywords: Telecommunications Abstract In the present work, the "historical developments in transport and telecommunications." Incorporates which actions can be replaced by new and what remains stable. There is a business directory which shows how professional groups affected by the evolution of telecommunications universal. How to change actions at work. How to change the working hours and the type of work. The research direction is practically the "automation and substitution projects and procedures" to work but which in turn allows the substitution probably offices (buildings). So changing and the cost of the rent and buying office. There could be different systems substitution similar as is cost technology and skilled personnel. We used methods for MCA. Wait to see how it has adversely affect the "external costs." 1) What will be the impact of telecommunications on the job. 2) The inclusion and valuation of external costs in labor and the use of external costs in addition to the total cost. This thesis will contribute to scientific research approaching the following key questions. There is potential for improving the way the use of telecommunications? How can we make the substitution of labor by telecommunications? There is clear evidence that these resources will be used in this survey (external costs) will reduce the total cost of labor? What are the economic implications of using this technology?


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Improvements and comparison of non-Euclidean metrics in minisum problem I. A.Osinuga*, L. A.Kazakovtsev Department of Mathematics, Federal University of Agriculture, Abeokuta, Nigeria * email of corresponding author: [email protected] Keywords: Location, optimization,class of metric, real life problems Abstract The planar location problem has been studied for many years. Yet, a number of important real world issues and variants have not been investigated and merit further attention. This paper describes new statements of the problem with new and different metrics, their properties and relationship existing between them. These enumerated and proposed metrics are special case of the class of metrics that not only give a good characterization of distance but also provide better interpretation of travel distances especially for real life location problems.


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Scheduling with a due-window for acceptable lead-times E. Gerstl*, G. Mosheiov School of Business Administration, The Hebrew University, Jerusalem, Israel * email of corresponding author: [email protected] Keywords: scheduling, single machine, parallel machines, due-window, lead-time Abstract Due-dates are often determined during sales negotiations between customers and the sales team of the firm. In the preliminary (pre-sale) stage, the customer provides a time interval (due-window) of his preferred due-dates. This interval reflects acceptable lead-times, which are functions of the customer resource constraints (e.g. storage or personnel limitations). If the due-dates are assigned either prior to or after the due-window, the firm is penalized accordingly. The final contract refers to the penalties of the actual delivery times as well. Thus, for given (realized) due-dates, the firm is also penalized according to the earliness/tardiness of the delivery time of the products. The model introduced in this paper considers both parts of the sales negotiations (i.e., determination of the time interval for acceptable due-dates, and earliness/tardiness penalties of the actual delivery times). Scheduling literature contains three major procedures for assigning due-dates to jobs: (i) assigning a common due-date for all the jobs (also known as CON), (ii) assigning job-dependent due-dates which are (linear) functions of the job processing times (also known as SLK), and (iii) assigning job-dependent due-dates which are penalized if exceed pre-specified deadlines (also known as DIF). One extension of these models is to a setting of due-window. In this setting, jobs completed within a time interval (rather than at a time point) are not penalized. Jobs completed prior to or after this time interval (window) are penalized according to their earliness/tardiness. The extensions of CON to a setting of common due-window (also known as CONW), and that of SLK to a due-window (SLKW) have been solved and published. The extension of DIF to a due-window is presented in this paper. The original DIF model reflects the fact that there exists "lead time that customers consider to be reasonable and expected". Thus, no cost is incurred when the due-date is assigned to be smaller than the maximum acceptable lead-time, and it is a linear function of the difference between the due-date and the maximum acceptable lead-time, otherwise. In our new more general model, a lower bound on the interval of acceptable lead times is assumed as well. As a result, if the due-date is assigned to be within a given interval of acceptable lead times (which is bounded both from above and from below), no cost is incurred. Otherwise, the cost is a function of the deviation of the due-date from this interval. While the original DIF model was shown to be solved in polynomial time in the number of jobs, the extension to a due-window setting is shown here to be NP-hard in the ordinary sense. We prove several properties of an optimal schedule, and consequently propose a very efficient dynamic programming algorithm. Our proposed algorithm is shown to be able to solve to optimality instances of up to 1000 jobs in reasonable time. Then, we extend our DP to a setting of parallel identical machines. The running time remains pseudo-polynomial, verifying that the problem remains NP-hard in the ordinary sense. We also introduce an efficient greedy heuristic and a tight lower bound. We evaluated the heuristic performance through numerical tests on large size problems. Extremely small optimality gaps are obtained.


Book of Abstracts

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Modelling a merge in network of warehouse facilities with two modes of operation: cross docking and traditional warehousing M. Vidalis*, P. Reklitis, V. Vrysagotis Mihalon 8 Chios Greece, 1st km Old National Road Athens- Thiva, Thiva, Greece, Tsikilitira 44 Maroussi, Greece * email of corresponding author: [email protected] Keywords: warehousing, cross docking material flows, traditional warehousing material flow, merge-in system, Markov analysis, performance measures Abstract The advent of the new warehouse technique of cross docking has created a new field of system modeling, this of warehouse stochastic modeling. In this framework, we deal on our paper with the analytical modeling of a dynamic supply system with two stages or echelons (supplier warehouses, distribution center). The system has an divergent structure, for this reason our model is entitled as merge- in. Further, there is no buffer in the system and the operation strategy is characterized as push. Our research methodology is the configuration of an analytical model representing the physical warehouse system as described above and the development of a computational algorithm. As far as the model concerns, we model the processing times for the two modes of material flow (cross docking material flow and traditional warehousing material flow) using Coxian-2 phase type distribution. The members of the warehouse system are functionally related. Supplier warehouses are assumed saturated. We use continuous time Markov process with discrete space to model the warehousing system. The steps for the development of the computational algorithm consist of the configuration of the state space and the transition matrix , the derivation of steady state probabilities and the calculation of the performance measures such as customer service targets (fill rate), average inventory (Work in Process- WIP) and the throughput, the rate the entities, material flows exit the warehouse system. Further, owing to a number of numerical experiments which are taken place, a warehouse manager can explore the behavior output variables (performance measures) of the model in relation with a sum of input and fully controllable (by the warehouse manager) variables. In more detail, we analyze the behavior of throughput in relation with distribution center processing rates and the fraction of cross docking orders. Moreover, the impact of the number of suppliers and the distribution center mean processing rates on the WIP is evaluated. Last but not least, the impact of the number of suppliers and distribution center mean processing rates on fill rate is examined. The above mentioned methodology offers to warehousing system administrators a research tool of system characteristics, being the contribution of our paper. The profound gain is useful conclusions for the warehouse operations and new ways of warehousing system optimization.


Book of Abstracts

2nd



Theory of attractive quality and multicriteria analysis: Analyzing customer preferences on smartphone attributes I. Pologiorgi*, E. Grigoroudis School of Production Engineering and Management, Technical University of Crete University Campus, Kounoupidiana, GR73100 Chania, Greece * email of corresponding author: [email protected] Keywords: Kano model, MUSA (Multicriteria Satisfaction Analysis), WORT (Weights, evaluation using Ordinal Regression Techniques), smartphone Abstract The quality of products and services is a key factor for the success of a business and it’s primarily determined by the customers’ needs and expectations. This justifies the necessity for identifying and analyzing customer needs and preferences. Although several approaches for measuring and analyzing customer satisfaction have been proposed, most of them adopt a one-dimensional recognition of quality with limited explanatory power. In particular, the one-dimensional view of quality can explain the role of certain quality attributes where both satisfaction and dissatisfaction vary in accordance with performance. However, this approach cannot explain the role of other quality attributes where customer satisfaction (or dissatisfaction) is not proportional to their performance. In this case, fulfilling the individual product/service requirements does not necessarily imply a high level of customer satisfaction (or the opposite). In this context, the Kano’s model, which adopts the theory of attractive quality, classifies the quality attributes into different quality dimensions: must-be quality, one-dimensional quality, and attractive quality. The Kano’s model may give insight into the relationship between the importance of quality attributes and the customer requirements for these attributes. Customers may be communicating different levels of importance in their explicit judgments of importance. In simple words, the theory of attractive quality suggests that the importance of a quality attribute is not constant, but it is affected by the category in which this attribute is assigned, as well as its performance level. The main aim of this study is to present a methodological approach in order to define different quality levels and classify customer requirements. The approach is based on Multicriteria Decision Analysis and adopts the principles of the Kano’s model. In particular, the main objective is the comparison between derived and stated importance for the satisfaction criteria. Stated importance is defined as the straightforward customer preference for the weight of a satisfaction criterion, while derived importance is estimated by a regression-type quantitative technique using customer judgments for the performance of this set of criteria. Both stated and derived importance are estimated using ordinal regression techniques and these results are comparatively examined through a dual importance diagram that defines different quality levels in agreement with Kano’s approach and gives the ability to classify customer requirements. The applicability of the proposed approach is illustrated by a real-world application in the mobile phone industry. In particular, the results of the presented customer satisfaction survey are focused on the quality attributes of smartphones. These results can give valuable information, since they may identify unspoken motivators or even expected or cost of entry attributes. Using this approach, customer requirements are better understood, since the product/service criteria that have the highest impact on customer satisfaction or dissatisfaction can be identified and priorities for product development may be decided.


Book of Abstracts

2nd



A hybrid fuzzy MCDM approach for evaluating financial performance of Iranian companies A. S. Ghadikolaei*, S. K. Esbouei Iran-Mazandaran-Babolsar-Mazandaran University * email of corresponding author: [email protected] Keywords: Financial performance, Accounting measures, Value based measures, Fuzzy Analytic Hierarchy Process (FAHP), Fuzzy Additive Ratio Assessment (FARAS) Abstract In a competitive environment, characterised by the scarcity of resources, performance evaluation and management play a crucial role. One of the main aspects of the organization performance is financial aspect which traditionally be attractive. Because profit is the main goal of many companies, financial performance and evaluation is very important. Most of the economical, industrial, financial or political decision problems are multi criteria. The application of multi-criteria decision making methods significantly improves the robustness of financial analysis and business decisions in general. In this study a new hybrid approach is used for financial performance evaluation of automative group of Tehran stock exchange (TSE). For this purpose, a hierarchical model with Accounting measures and Value based measures is structured. Fuzzy analytic hierarchy process (FAHP) is applied to determine the weight of criterion. The companies are ranked according their financial performance by using fuzzy additive ratio assessment (FARAS) method. Therefore, the finding of this study can help companies identify the important financial measures for have a better recognition of their financial performance.


Book of Abstracts

2nd



Staff Attraction And Selection Methods: The Case Of Mobile Telecommunications Companies In Greece M. Skordoulis*, M. Chalikias Technological Education Institute of Piraeus, Technological Education Institute of Piraeus * email of corresponding author: [email protected] Keywords: staff attraction, staff selection, human capital, mobile telecommunications companies in Greece, factor analysis. Abstract The purpose of this study is to examine the staff attraction and selection methods emphasizing the mobile telecommunications companies in Greece. This study is of great importance as staff attraction and selection are fundamental processes for modern enterprises. Human capital is of great importance for the enterprises due to the fact that employees have become an important element of strategies leading them to a competitive advantage. The focus on the mobile telecommunications companies derives from the fact that this is a constantly developing business sector which has increasing needs for human capital. The aim of this study is to examine and analyze the staff attraction and selection methods used by the mentioned companies as well as the factors associated with them. The evaluation of these methods based on the views of the employees is a further objective. The study of the motives provided by the companies to their employees is important as well. Data from 421 questionnaires answered by people employed in the three major mobile telecommunications companies in Greece have been statistically analyzed using descriptive analysis, factor analysis, cross tabulation, regression analysis, and hypothesis testing. The cited literature data have contributed to a better understanding of the research results. The research results were very interesting since the understanding of the factors concerning staff attraction and selection satisfaction became feasible. The statistical analysis revealed that the most widely used way of applicants attraction is through newspapers. On the contrary the least used way it through the social media. Yet, the analysis showed that employees consider the interview as most the most appropriate selection method. Hypotheses tests showed that the employees agree with both attraction and selection methods used by the examined companies. As far as the motives are concerned, the most important is the meet of the employees’ expectations, while the least important is the prestige of the position. The study of the research results shows that the mobile telecommunications companies operating in Greece should continue to use interviews as the major staff selection method. As far as the staff attraction is concerned the examined companies may have to focus a bit more on the use of social media. The main motive which should be provided is the meet of the employees’ expectations by their job position. These results may be used by the human resources managers in the staff attraction and selection process.


Book of Abstracts

2nd



Techno-Economic Evaluation of Energy-Saving Measures in a Public Building I. Papavasileiou*, V. Marinakis, J. Psarras National Technical University of Athens School of Electrical & Computer Engineering Management & Decision Support Systems Laboratory (EPU-NTUA) 9, Iroon Polytechniou str., 157 80, Athens, Greece * email of corresponding author: [email protected] Keywords: Techno-Economic Evaluation, Energy saving, Energy efficiency class, Energy-Saving Measures Abstract Nowadays, the building sector is responsible for at least 40% of the final energy consumption at national and European level. In Greece, 27,3% of the buildings are ranked at the lowest energy efficiency class H (most of them without thermal insulation) and 96,3% of the buildings lower than the reference building (energy efficiency class B). Taking into consideration their untapped potential for cost-effective energy savings, the penetration of energy efficiency technologies in the building sector could play an active role. The main objective of this paper is the energy saving study of a nursery school in the Municipality of Marousi, Greece. The building was constructed in 2008. In this context, the necessary data on the use of the electromechanical equipment were collected and analysed. An infrared camera was used to locate areas of extreme heat loss in the building, allowing for better insulating practices. The estimation of the annual electricity consumption of the building was made, based on relevant data from the Municipality of Marousi and Hellenic Electricity Distribution Network Operator. Moreover, the annual heat/cold energy consumption of the building was calculated, based on the use of relevant software and the estimated annual electricity and oil consumption. Based on the buildings’ consumption and requirements, a number of energy-saving measures were proposed. These alternatives were technically analyzed and economically evaluated with the Net Present Value (NPV), the Internal Rate of Return (IRR) and the Discounted Payback Period (DPB) criteria. It is estimated that the selected proposals will improve the energy efficiency of the building which will be ranked at the energy efficiency class A+.


Book of Abstracts

2nd



Development of a Multicriteria Decision Support System for selecting the most advantageous route of the produced biogas in Landfills S. Rogkakou*, N. Matsatsinis Decision Support Systems Laboratory School of Production Engineering and Management Technical University of Crete University Campus, 73100, Chania, Crete, Greece * email of corresponding author: [email protected] Keywords: Decision Support Systems, Renewable Energy, Landfill, Multicriteria Analysis Abstract The penetration of Renewable Energy (RES) in the electricity balance is significantly increased due to preferential Feed-in Tariffs (FIT). One of the RES is the evolved biogas at landfills Waste (Landfill) which is rich in methane. This study aims to create a decision support tool for landfill regarding the most advantageous route, economically speaking, between upgrading biogas injection to the gas versus electricity production from the raw biogas and bubbling to the electricity grid. For the analysis used the environment of MATLAB. The final decision will be based on the income that the algorithm using a multicriteria analysis method will calculate as it will determine the final amount of gas that can be absorbed by the grid or the quantity of electricity to be committed. The marginal prices of NG compensation are explored which is more lucrative diversion upgraded biogas into the grid NG to electricity production. Investigation is indicated on both Feed-in Tariff (FIT) prices and the marginal prices of electricity system. For these values is presented the expected amount to be injected into the natural gas grid, too.


Book of Abstracts

2nd



Heterogeneous management information software for supporting energy-related decision making problems I. Papastamatiou*, H. Doukas, J. Psarras 9 Heroon Polytechniou street, 15780, Athens, Greece * email of corresponding author: [email protected] Keywords: decision-making problems, heterogeneous information, software, 2-tuple fuzzy linguistic representation model, unification of non-homogeneous information, Basic Linguistic Term Set (BLTS) Abstract The energy alternative solutions of a decision-making problem can either be quantitative or qualitative by nature. The complexity of the solution frequently makes the use of non-homogenous information necessary in order to deal with such problems. Therefore, the use of non-homogeneous information in energy-related decision-making problems is not an unusual situation with proposals that combine numeric expressions of preference, fuzzy preference relations, multiplicative preference relations, utility preferences, preferences expressed by numerical intervals etc. However, most of the proposals for solving decision-making heterogeneity in the information focus on cases where the alternatives are expressed through real values, through value intervals or through linguistic labels that refer to a specific set of linguistic terms. In this paper, an information management tool has been developed, that implements successfully the three phases of the Herrera F. aggregation process for dealing with non-homogeneous contexts, taking as base the 2-tuple fuzzy linguistic representation model : (a) unification of the information, (b) aggregation of the preferred valued and (c) transformation into 2-tuple. The calculation is achieved through a powerful excel sheet that uses a lot of macros and Visual Basic (VBA) programming language. At first, the software unifies the heterogeneous information into a specific linguistic domain, which is a Basic Linguistic Term Set (BLTS), St. Each numerical, interval-valued and linguistic values is expressed by means of a fuzzy set on the BLTS, F(St). The process is carried out in the following order: (1) Transforming numerical values in [0,1] into F(St), (2) Transforming linguistic terms into F(St) and (3) Transforming interval-valued into F(St). Especially, for the transformation of the linguistic terms, an algorithm has been developed where the multivector sets S and St are divided into four separate segments, leading to a calculation that is divided into four different curves. Finally, the intersection points for each segment are calculated. In the 2nd phase, the tool aggregates individual performance values. For each alternative, a collective performance value is obtained aggregating the above fuzzy sets on BLTS. In the 3rd phase, the tool transforms the fuzzy sets into linguistic 2-tuples. Especially, for the calculation of the unification phase (a) of non-homogeneous information, up to our knowledge there is not such a mechanism proposed in the existing bibliography. The software, also offers a variety of additional options for the user. It allows the user to alter the BLTS and all the parameters in order to get multiple results quickly. The features described above assist any user that dealing with energy-related decision-making problems by allowing him to unify non-homogenous information in a fast and ground breaking way.


Book of Abstracts

2nd



Energy Consumption Evolution process V. C. Kapsalis* 9, I. Polytechniou Str., Zografou Campus, 157 80 * email of corresponding author: [email protected] Keywords: Energy consumption modeling; Empirical data performance; Markov properties; Brownian motion; Energy risk management Abstract One of most challenges in energy consumption modeling is the limited amount of historical and forward – looking information. This forces us to augment the standard techniques to extract as much as possible information we can. Consequently, the knowledge of distribution of energy consumption is a very important decision tool and contributes to a wide range of energy efficiency applications, from the energy conservation measurements establishment and the energy performance contracts development to the risk management strategies under uncertainty. Analysis of available data is the first, and potentially one of the most important steps in understanding and quantifying the essential features of the appropriate energy consumption model development. In this study, we focus in the special properties of consumption data, collected both of the utilities bills and a pilot installation of gas and electricity metering system in a university building. The energy consumption data analysis based on relevant statistical tools (ANOVA) and methodologies as well as meteorological data for the corresponding period. The specific requirements of the measurement and verification needs define the appropriate compliance path to use. Several regression techniques are examined to express the energy consumption’s relationship in a yearly base with multiple independent variables modeling the appropriate one. The baseline consumption is approached and successfully correlated with variable -based degree day model for both gas and electricity consumption. Moreover, the day ahead scheduling in liberated markets requires better insight in modeling techniques to accurately capture the structural characteristics of the empirical data and to manage the risk derived from scheduled and real energy market distortions. In deregulated markets the approaches could be quite different from those utilities have adopted for planning purposes in a regulated frame. The former analysis of energy consumption and temperature revealed, in some cases, the stochastic features of the distributions. Therefore, already well known processes in the financial world are examined to model continuous time processes. Brownian motion, expressed in several types, is one that has successfully used to describe and match the features of such time series. Here, we examine it to model the stochastic features of the energy consumption and temperature evolution derived from real data. Departing from the analysis of Markov properties existence, the distribution’s higher moments are tested and an alternative way to predict the forward consumption and temperature values is used and presented. Eventually, the difference between the of long and short term distributions expands the opportunities of further risk management solutions within uncertain environments.


Book of Abstracts

2nd



Agent based modelling and simulation for fuelwood consumption prediction E. Zografidou, I. Sakellariou*, K. Petridis, G. Arabatzis University of Macedonia, 156 Egnatia street, 54006, Thessaloniki, Greece * email of corresponding author: [email protected] Keywords: ABMS, Supply chain, Price prediction, Fuelwood, Biomass Abstract Biomass fuels present an increasing source of energy for heating in Greece mainly due to the increased oil domestic prices and the economic recession. Fuelwood, presents one of the most important types of biomass used for heating (wood-burning) by households today, with an increasing trend in its adoption as either a primary or a secondary source of energy. The forest supply chain (FSC) consists of several nodes and operations, essential for the production and transportation of wood products from the starting node, i.e. the forest site, to the end node, i.e. the individual household consumer. In the case of Greece, fuelwood logging mainly is conducted by Agricultural Forest Cooperatives (AFCs), that are assigned to specific forest compartments. The next nodes in the chain are warehouses, where fuelwood is transported after logging, and which assume the role of distributors to the end customers. Price may depend on a number of factors such as fuelwood production, weather conditions, distance from logging site, customer behaviour, etc. Although a number of models have been used to tackle the problem, this work proposes Agent Based Modelling and Simulation (ABMS) as the tool of choice for fuelwood market modelling. Under ABMS, each node in the supply chain is modelled an agent, dynamically determining its behaviour in the environment according its individual preferences and parameters. This dynamic behaviour is governed by a set of rules, derived from statistical analysis of questionnaires distributed to the involved parties. The model also accommodates market processes that take place between AFCs and warehouses and between the latter and final consumers. The results obtained concern the flow of fuelwood quantities, logged, stored in warehouses, and consumed by households and most importantly, fuelwood selling price is predicted under different scenarios of demand, supplied quantities and different consumer's policies (pricing, auctioning). This microsimulation approach, allows for more accurate and flexible modelling of the market, and provides the necessary tools for experimentation under different conditions.


Book of Abstracts

2nd



Designing A Practical Dynamic Lead-Time Quotation Policy In A Make-to-Stock Queue G. Kahvecioglu, B. Balcioglu* Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, 34956, Turkey * email of corresponding author: [email protected] Keywords: dynamic lead-time quotation, order acceptance, make-to-stock queues Abstract We design two dynamic lead-time quotation policies, which can most suitably be applicable in a business-to-business setting. The production/inventory system of a single supplier is modeled as a make-to-stock queue, and the demand for a single type of product manufactured is assumed to follow a Poisson process. The production control is carried out according to a base-stock level policy. Demand requests are satisfied right away as long as there is stock on hand. If there is no stock on hand and a new customer appears, the supplier announces a lead time by the end of which it promises to deliver the product. The lead time announced dynamically changes with the number of already backlogged customers. Depending on the lead time announced, the customer may choose to place an order or is lost. If the supplier fails to deliver the product within the lead time, it incurs a penalty cost proportional to the length of the additional delay. The first policy we propose makes use of the sojourn time distribution of the new order and the fraction of customers for which the supplier is willing to incur the penalty cost. Since this policy gives the same probability of delivering the finished good for any backlogged customer, we call it the Fair Quotation (FQ) policy. Unless the customers are oversensitive to the announced lead times, the FQ policy performs close to the optimal policy that was characterized for systems with exponential service times. The second policy is a refinement of the FQ policy, which aims at alluring/deterring more customers with respect to the FQ policy when the backlog queue gets short/long. Thus, we refer to it as the Preferential Quotation (PQ) policy. Via numerical examples, we show that for over-sensitive customers the PQ policy turns out to be the optimal policy most of the time. The real advantage of these two policies is that they are applicable for any delay system for which the sojourn time Laplace transform can be obtained. We also implement them when the service times are non-exponential for which the optimal policy is difficult to characterize, and observe how the variability in service times affects the profitability of the system.


Book of Abstracts

2nd



Performance analysis of power saving methods in wireless systems with retransmissions: A queueing theory framework I. Dimitriou* Department of Mathematics, University of Ioannina, 45110, Greece * email of corresponding author: [email protected] Keywords: Power saving, Queueing theory, Modified multiple vacations, Retransmissions Abstract Wireless networks have enjoyed the exponential development, and wireless communication has become an essential part of modern life. Many new wireless applications demand higher speed and consume more energy. However, wireless devices are always powered by batteries, which have limited life time and constrain the use of wireless devices and the growth of wireless networks. Energy efficiency becomes an important issue in wireless networks and power management is a method that can save energy. Moreover due to the mobility, the limited battery and wireless interface the channels with the mobile devices are often disconnected. A traditional way to obtain reliability in wireless communications is repetition using retransmission protocols. In the general case when the transmission fails it is assumed that it will be attempted again until a success. In this paper we investigate the power management of mobile devices by a variant of a M/G/1 queue with probabilistic inhomogeneous multiple vacations and timers. We assume that the service process consists of at most two cycles. First cycle consist of at most N independent arbitrary distributed service periods Bi. Upon the completion of the ith service period, the service procedure is succesful with a certain probability. Otherwise, an (i + 1) service period is required. If N consecutive service times are not satisfactory, the server switches to the second service cycle. During the second service cycle the server provides at least one arbitrary distributed service time B0. Under the modified multiple vacation scheme, at the end of a vacation the server goes on another vacation, with a different probability distribution, if during the previous vacation there have been no arrivals. Each vacation period consists of a sleep and a listening period. The modified vacation policy depends on the initial vacation period and the server has the opportunity to select over M such vacation policies. The theoretical system can be applied for modelling the power saving mode of a mobile device in modern wireless communication systems such as 3GPP LTE and mobile Wimax. The sleep period refers to the time period the device turns off its physical components in order to save energy and corresponds to the modified vacation policy. At the end of that period wakes up to listen the physical downlink control channel for pending packets. If there are packets in the base station, the device switch to the normal mode in order to receive them. Otherwise, it enters the next sleep period. Moreover the form of the service process can describe the incremental redundancy Hybrid Automatic Repeat Request (HARQ) process that provides different types of retransmissions in such systems. Using Markov chain analysis we investigate the steady state analysis and stability while using results from regenerative analysis we obtain useful performance measures regarding the state of the server. Stochastic decomposition is also discussed. Several energy metrics, such as the Power Saving Factor, the energy efficiency and the expected power consumption of the device are obtained and used to provide useful numerical results that give an insight to the system's performance.


Book of Abstracts

2nd



A batch constant retrial queue with multiple adaptive vacation policy G. C. Mytalas*, M. A. Zazanis Athens University of Economics and Business * email of corresponding author: [email protected] Keywords: adaptive vacations, constant retrial Abstract This paper considers a batch arrival retrial queue with general retrial times under a multiple adaptive vacation (MAV) policy. Any arriving batch finding the server busy or on vacation enters an orbit. Otherwise, one customer from the arriving batch enters for service immediately while the rest join the orbit. When the orbit becomes empty the server takes a string of vacations, independently of the history of the process up to that point with some fixed probability, during which any customers that arrive wait in orbit for service. At the end of the vacation, if no customers are present in the queue, the server may remain idle and available for service, or take another vacation. The total number of such vacations follows a given discrete distribution. By applying the supplementary variables technique, some important system characteristics are derived such as the stationary queue length distribution, the sojourn time of the typical customer in the stationary regime, and the distribution of the busy period.


Book of Abstracts

2nd



Ordering policies for two products with demand substitution O. Kanavetas*, A. Burnetas University of Athens Department of Mathematics * email of corresponding author: [email protected] Keywords: Adaptive Ordering Policies, Inventory Abstract We consider the problem of ordering for two products with stochastic demand and partial demand substitution. Successive demands arrive at random times, thus the order of arrivals affects the ending inventory and/or shortages. We define an equivalent queueing model, compute steady state performance measures, and analyze monotonicity and submodularity properties of a suitable average profit function. Finally, we consider extensions to the case of unknown parameters and suggest adaptive ordering policies.


Book of Abstracts

2nd



Customer Equilibrium Policies in Observable Queues for Multiple Periods A. Burnetas* University of Athens * email of corresponding author: [email protected] Keywords: Queueing Theory, Games in Queues Abstract We consider a multiperiod equilibrium model in a Markovian queue. Arriving customers observe the queue length upon arrival and decide whether to join the queue, or not join and postpone the decision for the next period, while in the last period the decision is join or balk. The queue reaches a steady state within each period. We show that there exist multiperiod equilibrim threshold strategies. We also consider the problem of social welfare maximization in the multiperiod setting.


Book of Abstracts

2nd



Evaluating new service development effectiveness in tourism: An ordinal regression analysis approach F. Kitsios* (1), E. Grigoroudis (2) (1) School of Informatics, Department of Applied Informatics, University of Macedonia, (2) School of Production Engineering and Management, Technical University of Crete University Campus, Kounoupidiana, GR73100 Chania, Greece P.O. Box 1591, GR54006 Thesaloniki, Greece * email of corresponding author: [email protected] Keywords: New service development, strategic innovation management, tourism, ordinal regression analysis Abstract Innovation development is an important factor for the viability and profitability of service businesses operating in modern markets. The importance of the service sector in developing economies and the specific characteristics of services compared to tangible products require further investigation in the New Service Development (NSD) process and effectiveness assessment when innovations applied. The innovation development process will be significantly improved and the contribution of innovations in company’s goals will be substantial. The purpose of this study is to evaluate the effectiveness of the NSD process in the tourism economy and in particular the Greek hotel sector. For this purpose, factors influencing the process of developing new services in the hospitality sector were explored and correlated with the financial results of the hotel enterprises through an ordinal regression analysis model. The model adopts a mathematical programming (goal programming) approach in order to estimate the efficiency of this process. In the presented study the Greek tourism industry and its importance to the national economy is discussed. The study explores in detail the factors influencing the NSD process. The questionnaire developed for the purpose of the survey included a large number of variables related to all the stages of the NSD process (from idea generation till the service launch). All variables are measured in a 5point Likert type scale and data was collected using in depth structured and questionnaire-based interviews with 77 hotel managers for 147 new services in a representative sample of 99 hotels in Greece. Several financial ratios covering different aspects of the business (e.g., profitability, liquidity, activity) are used in order to evaluate the NSD process for three years after the services innovation had been launched. The main results of the ordinal regression model include the estimated contribution of each factor to the financial performance of the hotels studied.


Book of Abstracts

2nd



A Decision Support System for Choosing Higher Education Studies M. Vassilakopoulos*, V. Kostoglou , N. Ploskas

University of Thessaly, Department of Computer Science and Biomedical Informatics 2-4 Papasiopoulou st., 351 00, Lamia, Greece


Keywords: Computer assisted studies guide, Decision support system, Higher education, Specialty of studies, Vocational orientation.

Abstract

The selection of higher education (HE) studies by the lyceum graduates, and the vocational orientation of students and fresh university graduates present particular interest for the majority of each country’s youngsters. Despite their prime importance, these issues, as well as linking between HE and labor market constitute research areas that have not been investigated extensively. Nevertheless, these areas present exceptional interest and practical implications because they are directly connected to the desired decrease of the unemployment rate, one of the top priorities at personal, state and European level. Among the tools used in vocational orientation and in career planning and development are the job profiles; a basic or detailed description of the different professions, in a standardized way, recorded in most cases in digital databases, accessed easily through computer applications. A job profile includes any type of information that defines the inputs, process and outputs of any job, such as statements, roles & responsibilities, expected results, required skills & qualifications, experience etc. associated with the job or the person doing the job. The usefulness of job profiles is apparent: the professions of each broader specialty mirror the current situation of the corresponding labor market. In previous work, the authors presented the analysis and design of a digital guide. The proposed web-based Decision Support System (DSS) informs and assists its users for the available HE studies in Greece. The users of the DSS are classified into two categories: i) youngsters that want to choose the most appropriate for them HE studies, and ii) students and graduates searching for information about their specialty's vocational prospects. The digital guide presents the provided specializations by the Greek HE; the corresponding departments are categorized according to their specialty, their vocational prospects and HE institutions. These categories offer the opportunity to the users to search the DSS database according to their criteria. In this work, the authors present features and functions that enhance their previous work and empower the digital guide. These include: • The details of the user-friendly interfaces that allow the user to interact with the DSS, simply and powerfully, whatever the category (e.g. desktop PC, tablet, smartphone) of the device he/she uses. • The SQL queries that the interaction of the user with web interface of the digital guide fires. • Embedding in the job profile database historical data that help to answer aggregate queries (e.g. which is the current entry grade as well as its trend for entering to a department, or to departments belonging to a specific school, or to a specific geographical area). • Embedding in the job profile database data related to the placement of graduates of each higher education specialty on the labor market. • The design of new services to the DSS users, such as: i) Support of personalized user information, provided by the user him/herself through wizards and successive questions, and ii) Apart from “pumping out” exact information existing in the job profile database based on the criteria entered by the user, the DSS can also use criteria and information provided by the user to form recommendations for his/her choice of job/study specialty. Based on the material presented in this work, the authors plan to develop a powerful DSS able to inform its users about the current provided HE studies in Greece, and most importantly to assist them in their selection of HE studies aiming at a smooth and prompt future entrance in the labor market, and eventually promising professional career.


Book of Abstracts

2nd



A similarity metric for traces in Event Logs based on an outranking approach P. Delias*, M. Doumpos, E. Grigoroudis, N. Matsatsinis SDO Building, Agios Loukas, Kavala, Greece * email of corresponding author: [email protected] Keywords: Process Management, Multiple Criteria, Outranking Methods Abstract Given an Event Log (a collection of events and their sequences per case), Process mining techniques are able to discover the real process. However, there are domains like healthcare services or customer support, where there is not structured, strict process or even if there is such a process, involved actors are allowed to deviate from it, or even completely ignore it. In these cases, aiming to discover a simple process model can misguide process analysis. Therefore, instead of discovering a single process model, clustering traces and discover a model per cluster appears as a promising approach. In every clustering approach, a major decision is the similarity metric to be used. Although for business process similarity, many metrics have been proposed, few works focus on the trace similarity issue. These works use common geometric and related metrics. In this work we question how suited these metrics are for this problem and we propose a clustering method based on a valued similarity relation inspired by outranking methods. We consider the strength of both concordance coalitions as well as discordance coalitions. In addition, we discuss some properties of the proposed similarity metric such as non-negativity, symmetry and triangle inequality. This research has been co-financed by the European Union (European Social Fund) and Greek national funds through the Operational Program "Education and Lifelong Learning".


Book of Abstracts

2nd



Accounting information in the prediction of securities class actions V. Balla*, F. Pasiouras, C. Zopounidis Technical University of Crete, University Campus, Chania, Crete * email of corresponding author: [email protected] Keywords: Prediction, Securities Class Actions, Multicriteria techniques Abstract The imminent risk of filing a securities class action affects significantly investors’ decisions. The development of a model to predict securities class actions enables investors to determine the optimum portfolio of stocks, decide when to sell or buy a stock and as a result to maximize its return. The first objective of this paper is to examine the impact of accounting information to the classification of firms between securities class actions and non-securities class actions. The second objective is to develop multicriteria techniques in order to predict the phenomenon of securities class actions. Data used are collected from industrial sector over the period 2003 and 2011. The contribution lies to the fact that it is the first time that a study examines the prediction of this phenomenon basing its data on the most recent period employing the largest sample so far.


Book of Abstracts

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Developing an ANP and Intuitionistic Fuzzy TOPSIS for Supplier Selection B. D. Rouyendegh* Technical University of Crete, University Campus, Chania, Crete * email of corresponding author: [email protected] Keywords: Prediction, Securities Class Actions, Multicriteria techniques Abstract The imminent risk of filing a securities class action affects significantly investors’ decisions. The development of a model to predict securities class actions enables investors to determine the optimum portfolio of stocks, decide when to sell or buy a stock and as a result to maximize its return. The first objective of this paper is to examine the impact of accounting information to the classification of firms between securities class actions and non-securities class actions. The second objective is to develop multicriteria techniques in order to predict the phenomenon of securities class actions. Data used are collected from industrial sector over the period 2003 and 2011. The contribution lies to the fact that it is the first time that a study examines the prediction of this phenomenon basing its data on the most recent period employing the largest sample so far.


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Evaluation of the operational performance of Greek public hospitals using a robust multicriteria approach G. Fragkiadakis, M. Doumpos*, C. Zopounidis Technical University of Crete, Dept. of Production Engineering and Management, Financial Engineering Laboratory, University Campus, 73100 Chania, Greece * email of corresponding author: [email protected] Keywords: Healthcare management, Hospitals’ performance, Multicriteria analysis, Robustness Abstract Throughout the world, healthcare systems have been under increasing pressure to improve performance by controlling healthcare costs without compromising the quality of the provided services and access to them. In Greece, particular emphasis has been put on implementing structural reforms in the healthcare sector in order to improve its efficiency and performance, taking into consideration the significant rise in public health expenditure over the past decade. In this context, this study introduces a multicriteria approach to the evaluation of the operational performance of Greek public hospitals. The evaluation takes into account criteria related to the hospitals’ costs, their human resources (clinical and non-clinical staff), and the type of services that they provide. Different scenarios are tested for the relative importance of the performance evaluation criteria, thus leading to robust conclusions with respect to the overall results. The empirical analysis is based on data for 87 Greek public hospitals over the period 2005-2009. The results indicate that medium-sized hospitals performed better than larger hospitals. The study also identifies differences between health districts as a result of the absence of national health strategic plan for performance evaluation and efficiency analysis.


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A stochastic location allocation model for primary health care network planning P. Mitropoulos*, I. Mitropoulos, I. Giannikos Department of Business Planning & Information Systems, Technological Education Institute of Patras, GR-26500 Patras, Greece; Department of Business Administration, University of Patras, GR-26334 Patras, Greece * email of corresponding author: [email protected] Keywords: Location-allocation; Stochastic programming; Demand uncertainty; Health care management Abstract To develop the strategic plan from a system perspective and effectively address the primary health care needs of its residents in the future we configure its services based on a data driven, evidenced-based methodology in alignment with population needs and leading clinical practice. The approach needed to be sufficiently flexible to consider different configurations of the system (e.g., number of clinical services for any given health center, degree of clinical specialization, options for future sites, and clarification of the health center service role) yet rigorous enough to ensure clinical standards are met while providing good access to the population. These strategic planning, decisions may have a long lasting effect and the implementation may take considerable time. Moreover, input data is not precisely known in advance. Hence, decisions have to be made anticipating uncertainty. In this paper, we address several aspects concerning a health services location problem under uncertainty. We present a stochastic mathematical programming model to provide options for configuring the system of primary health care focusing on the location of health services and allocation of residents among a predetermined number of health centers. The decisions in the model are based on population access, critical mass standards, and clinical adjacencies. Catching the balance in the spatial distribution of populations and services is one of the main problems in health centers evaluation. Two sources of uncertainty are considered: the public preference choice between hospitals and health centers of demand and the seasonal variation of demand. We describe an extensive scenario analyses allowed administrators, clinicians, and planners to test multiple system configurations, gain a robust understanding of the trade-offs between these configurations, and formalize the planning process for primary health care services. We aim at presenting generic models capturing the uncertainty associated with the data. By performing computational analysis, we analyze the changes in the solutions with different sources of uncertainty. Our aim is to get an insight on how relevant a modeling framework comprising uncertainty aspects may be the location health services. We study how solutions obtained under uncertainty differ from the solutions based on deterministic data. We consider a discrete type of uncertainty where uncertainty is represented by a finite set of scenarios. The elements of the problem are as follows: • Demand (existing and projected future patient demand, grouped into three clusters of clinical services); • Facility location constraints (34 health centers at present and options for future configurations); • Geographical variation (multiple communities, grouped into 103 local population centers). The final modeling framework, which combines uncertainty in the public preference and in the demands, is built throughout the paper.


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The Obstetric Services in the Attica Area: Concentration Ratio and Competition A. Petsa* (1), A. Vozikis (2) (1) Researcher, University of Piraeus, Department of Economic Science 80, Karaoli & Dimitriou street, 18534 Piraeus, Greece, Tel: 210 4142280 E-mail: [email protected] (2) Assistant Professor, University of Piraeus, Department of Economic Science 80, Karaoli & Dimitriou street, 18534 Piraeus, Greece, Tel: 210 4142280 E-mail: [email protected] * email of corresponding author: [email protected] Keywords: Obstetric services, Competition, Concentration, Attica, Economic crisis. Abstract Introduction: The Health System in Greece is a mixture of public and private sector. In several medical specialties, the private sector is the dominant one. Especially regarding the case of obstetric services, the private sector has almost taken the features of an oligopolistic market. Purpose: The purpose of this research is to estimate the intensity of competition in the private maternity-obstetric hospitals, during the period 2005 – 2012 in Greece and more specifically in the Attica area. Material and Methods: The data used in this research were collected from the published accounts and financial statements of the private maternity hospitals, as well as in various published studies in Greece. The research tools used, were those of globally accepted, Concentration Ratio (CR) and Herfindahl–Hirschman Index (HHI). More specifically, the revenues as well as the market shares of every maternity hospital were registered from 2005 to 2012, and then the two indexes were calculated. The data were analysed with the use of Microsoft Excel. Results: Our survey showed that there are basically five maternity hospitals in the Attica Area. During the period from 2005 to 2010, the dominant maternity hospitals in the Attica area were three (Iaso, Mitera, and Leto). They were summing up to the 100% of the market in the area of Attica and approximately the 80% of the market share in the whole country. A differentiation in the market share of the three dominant maternity hospitals was observed in 2010 with entrance of two new companies (Gaia, and Rea) in the market, as well as to the onset of the economic crisis in Greece. An even greater differentiation in the market shares was observed during the period 2011–2012, attributed to the austerity measures imposed to Greece and the subsequent reduction in the number of births. There was also a change in the first three dominant positions, as in the first and second position remained Iaso and Mitera, however, maternity hospital Rea has gained the third position, owing to the unique position that it possesses since it is the only one situated in the south area of Athens. Conclusions: The concentration of obstetric services is particularly high in the area of Attica. The variations in the two indexes, initiating from the year 2010, mainly due to the entrance of two new “players” in the market (Gaia and Rea) and to the economic crisis in Greece. The latter has resulted in the reduction in the number of births and the sift to the public maternity hospitals, in order to reduce the costs of the family budget. Finally, the entry of Rea –a new maternity hospital– among the three dominant in the area of Attica is attributed to its strategic and unique position, in the south area of Attica.




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Medical errors in Greece: Main research findings through Greek courts’ judgments A. Vozikis* (1), M. Riga (2), Y. Pollalis (3)

(1) Assistant Professor, University of Piraeus, Department of Economic Science 80, Karaoli & Dimitriou street, 18534 Piraeus, Greece, Tel: 210 4142280 E-mail:[email protected] (2) Phd Candidate-Researcher, University of Piraeus, Department of Economic Science 80, Karaoli & Dimitriou street, 18534 Piraeus, Greece, Tel: 210 4142353 E-mail:[email protected] (3) Professor, University of Piraeus, Department of Economic Science 80, Karaoli & Dimitriou street, 18534 Piraeus, Greece, Tel: 210 4142353 E-mail: [email protected]


Keywords: medical errors, medical malpractice, healthcare costs, health information systems, patient safety, quality health care

Abstract

Objectives Recent research in Europe and the USA revealed that the number of patients who have experienced a medical error in healthcare has increased worryingly since the last decade, while over half of harm refers to medical errors reasonably preventable. At the same time, surveys indicate that medical errors constitute a significant financial burden on Health Care Systems. Based to a recent Eurobarometer survey, Greece ranks first among EU27 as more than eight out of ten Greek citizens feel it is likely they will be harmed by healthcare, whilst 16% of respondents or a member of their family have experienced an incident. The innovation of this paper is to attempt a survey of the current situation in Greece through the judgments of civil and administrative courts. Methodology It was conducted an extensive analysis of 287 cases associated with medical malpractice and were presented to Greek courts over the last 10 years. The research process included a detailed review of the case and economic and other data where recorded. Then simple descriptive statistical analysis was applied to unveil information relevant to our survey. Results The findings from our analysis on various assumptions of public and private hospitals are compatible with other international studies and reports. About 68% of legal actions brought against public hospitals and 18% in private hospitals and medical centers. Some 45% of medical errors occur during treatment while most incidents of medical error related to death (37%) or permanent disability (36%). Further, the survey unveiled that on top of the list of specialties who are involved in cases of medical errors are the specialty of General Surgery and Obstetrics - Gynecology. Additional findings from the survey also show that the average amount of financial compensation awarded by courts, indicatively mention, is €623,146 for the specialty of Obstetrics - Gynecology, €324,901 for the specialty of General Surgery and €319,771 for Anesthesiologists. Conclusions From our research, it was found that in Greece the economic burden of medical errors on the Health Care System appears to be worryingly high. In Greece, unlike other countries in the world, the assessment of an overall burden of medical errors is not achievable, mainly due to the absence of any medical error reporting system. The development and implementation of Medical Error Reporting Information System (MERIS) in order to detect, record and analyze medical errors nationwide is paramount in order to achieve control of the problem. Above all, the aim of MERIS is to become a useful tool for health providers, to enhance both patient safety and quality health care, with major prerequisites the co-operation and trust between patients, health care professionals, hospital managers and government.


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Assessment of Policy Interrelationships and Impacts on Sustainability in Europe - Empirical Analysis of the Energy & Climate Package APRAISE Consortium, Presentation by N. Spyridaki*

9 Heroon Polytechniou street, 15780, Athens, Greece


Keywords: Energy and climate policy interactions, quantitative and qualitative approaches, efficacy, context, design and implementation

Abstract

Assessment of Policy Impacts on Sustainability in Europe” (APRAISE) aims at enhancing policy makers’ insights on the effects of (a set of) policy instruments toward environmental goals and sustainability. For this, the project takes as a starting point that policy makers, when designing policies and selecting policy instruments, make use of the best available knowledge of how policy instruments work in terms of direction and strength towards achieving a goal and how goals can be achieved with lowest resources. In reality, however, the optimal outcome which policy makers expect to achieve by means of a given set of policy instruments (based on efficacy knowledge) is often not realized in practice. In other words, the actual effect of policy instruments (effectiveness) could in practice deviate from expectations. Such deviations are explored in APRAISE by evaluating case studies in six categories in seven EU Member States (Austria, Estonia, Germany, Greece, the Netherlands, Slovenia and the UK, with a specific focus on whether:(1) the economic or political context for policy instruments was different from the one expected, (2) the implementation of the policy instrument was hampered or facilitated unexpectedly, or (3) interactions of the assessed policy instrument with other policy instruments gave rise to deficiencies or synergies. In addition to a policy evaluation with help of environmental policy case studies, APRAISE also applies a set of modeling instruments to assess the influence of environmental policy instruments on the state of the environment and sustainability more generally. With this more quantitative approach ex- ante views (scenarios) can be developed on how implementation of policy instruments leads to the adoption of environmental technologies and how this supports ecological sustainability and economic performance. In APRAISE, modeling elicits the effects a policy instrument is expected to exert under optimal conditions (efficacy) and the relation of these effects to the incurred costs (efficiency). A variety of models is used in APRAISE for efficacy and efficiency assessments, which basically serve two different purposes. The Business Strategy Assessment Model (BSAM) models the decision-making process of power suppliers concerning the technologies employed for producing electricity. This combined model also shows how this decision making process is influenced by relevant environmental policies. This approach will thus represent the bottom-up perspective to the efficacy and efficiency of environmental policy instruments and provide us with ideas as to how many environmental technology devices are or will be installed and what their environmental effects will be. By contrast, the model Global Trade Analysis Project (GTAP) in combination with VTT TIMES, models the macro-economic effects arising from environmental policy instruments and the investment in the corresponding technologies induced by them. The effects include the impact of these investments on growth, employment and foreign trade. This group of models assumes a “social planner” perspective, looking at, and assessing, the relevant policy effects from a top-down perspective. While both bottom-up and top-down approaches are able to model the combined, cumulated effects of several policy instruments, only the former can model policy interaction endogenously – showing how one policy instrument possibly supports or inhibits another one in achieving its intended effect. In APRAISE, a broader understanding of interaction is employed, including for instance policy instruments affecting the


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environmental policy to be assessed, but being employed in other sectors and intended primarily to address completely different issues. Hence, quantitative modeling will be used in combination with the case studies. The qualitative parts will assess the diversity and complexity of policy interactions, while the quantitative (modeling) parts contribute absolute figures and the basic trends governing them.

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Development of a knowledge platform on post Kyoto climate policy implications POLIMP Consortium, Presentation by A. Flamos* 9 Heroon Polytechniou street, 15780, Athens, Greece * email of corresponding author: [email protected] Keywords: Climate policy, post-Kyoto agreement, socioeconomic implications, knowledge platform Abstract The starting point for POLIMP is the current state of play of climate policy negotiations under the UNFCCC with an objective to limit global average temperature increase to 2oC but with disagreement on how to distribute costs of mitigation efforts and formulate countries’ climate policy ambition levels. Based on this background, the overarching motivation of POLIMP is to facilitate exchange and transfer of information about climate policy and its implications among policymakers, market actors and general society within the EU. This will be done by identifying where knowledge gaps exist and how these gaps can be filled. The aim is to provide stakeholders with better insights on implications of possible international climate policy directions, so that they can take well-informed decisions with reduced uncertainties and mitigated risks. To achieve that, POLIMP will: (a) build upon knowledge of the existing and future climate policy developments, which will be efficiently assimilated, (b) provide the existing stock of evaluation outcomes of various climate policy scenarios widely in a comparative manner, and (c) actively trigger the exchange of targeted information to targeted actors in order to promote effective and efficient climate policy implementation. Knowledge gaps will in turn be identified for a range of priority issues related to climate policy making in consultation with stakeholders, but as a starting point for discussion the following three (categories of) issues are suggested: • What would different possible international climate policy scenarios entail for EU society, business, Member States and EU as a whole, in terms of economic, social, and environmental impacts looking especially at likely reactions and resulting political acceptability for different groups such as those impacted by job losses and reductions in welfare as well as potential gains? • How can EU stakeholders deliberate in an evidence-based manner about the pros and cons of these different scenarios? • How can EU and EU stakeholders learn from design and implementation of climate policies worldwide as well as share the experience the EU has gained in designing and implementing

climate friendly actions

In turn, POLIMP will process these collected data and knowledge into the following information packages:

- The effectiveness of possible future international climate policy regimes in addressing climate change mitigation and adaptation needs and resulting objectives. - Projected socio-economic impacts of possible international climate policy directions for different stakeholder groups within the EU. - Opportunities for the EU and EU stakeholders to learn from design and implementation of climate policies worldwide, as well as share the experience the EU has gained in designing and implementing climate friendly actions, including the EU emissions trading scheme, sector benchmarking and technology development and transfer.


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These information packages will be communicated with stakeholders through workshops. In addition, the information will be made available through an online Knowledge Platform, which will be constructed for this project. The main objective of the platform is to address knowledge gaps by presenting complex facts and data in easily understood language and in intuitively understandable structure and searchable format. Finally, POLIMP will draw lessons learned from the comparison of possible directions of

futureclimate policy making and implications of these for international climate targets and EU climate, economic, environmental and social goals. It will incorporate lessons learned

from the stakeholder assessments, knowledge gap identification and data collectionand knowledge processing work. With these insights, recommendations can be formulated for stakeholders at different policy and decision making levels within the EU, which will support

the formulation of futureEU climate, economic, environmental and social policy making and enable stakeholders to effectively and efficiently deal with these policies.

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A method for predicting electrical consumption in energy-intensive buildings through energy performance indicators E. Spiliotis*, A. Raptis, N. Z. Legaki, V. Assimakopoulos Agiou Andreou 13, Nea Smyrnh, Athens * email of corresponding author: [email protected] Keywords: forecasting techniques, energy saving techniques, energy performance indicators, energy assessment Abstract The aim of this paper is to develop a methodology with which it is becoming possible to predict the electrical consumption in energy-intensive buildings, such as restaurants, offices, hotels, hospitals and supermarkets, through a range of energy performance indicators. Specifically, the most representative indicators per energy consumption group of the building (HVAC, lighting, kitchen, refrigerators, etc.) are defined and time series forecasting methods are applied at its time series, in order to predict and evaluate future energy performance of the building. The existence of such a forecasting methodology is particularly useful nowadays, given the need of saving energy, due to economic and environmental reasons. First of all, the concept of index is presented, with particular emphasis given on the advantages that its adoption as a research tool provide, while a basic categorization of energy performance indicators is reported. In addition, the exposure of the forecasting methods that will be used is followed by definition of important accuracy metrics and description of the best technique's selection process, which is realized through error minimization. Finally, the developed forecasting methodology is presented in detail and two case-studies are presented, in order to determine the effectiveness and the accuracy of the method. The first is taking place in a fast- food restaurant and the second in five different bank branches. The aim of the second case-study is not only to evaluate the forecasting method, but to compare also the future energy consumption of same type of buildings and detect which is performing more efficiently.


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Energy priorities’ identification for the municipality of Apokoronas for the reduction of its carbon footprint P. Konstantiou*, A. Papadopoulou, J. Psarras Decision Support System Lab, School of Electrical and Computer Engineering, National Technical University of Athens, Iroon Polytechneiou 9 Str., 157 73, Athens, Greece * email of corresponding author: [email protected] Keywords: Action Plan for Sustainable Development, energy and CO2 balance, energy saving, renewable energy actions, municipality of Apokoronas Abstract The Covenant of Mayors is a European initiative that aims to fight climate change through the promotion of energy efficiency and penetration of RES. Already a large number of municipalities at the European level has joined this initiative, while Greece numbers 81 signatories. In April 2013 the Municipality of Apokoronas signed the Covenant and pledged to reduce its CO2 emissions by at least 20% by 2020. In the above context, a study of the energy and carbon footprint of the municipality for the chosen base year (Action Plan for Sustainable Development) took place and a series of actions that promote the use of energy efficiency and renewable energy sources in all energy consuming sectors in the municipal territory are suggested. To carry out this study, thorough registration of the municipality’s energy consumptions took place, while there was close cooperation with a number of local stakeholders. In addition, data that could not be identified directly at the municipal level were estimated using scientific publications and studies. The identified actions contribute to reducing the carbon dioxide emissions by 21.54%. Furthermore, implementation priority is assigned to those actions depending on the potential energy savings, contribution to the reduction target of CO2 emissions and financial indicators, such as the cost of implementation by the municipality and the benefit for the citizens.


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Τhe Impact of Environmental Issues Upon Journalistically Mediated Nation Images: An Intercultural Content Analysis A. Samaras, J. A. Paravantis* Department of International and European Studies University of Piraeus * email of corresponding author: [email protected] Keywords: Quantitative Content Analysis; Environmental News; News Media; Framing; Instrumental Actualization; Nation Image; Valence; Visibility. Abstract News topics affect the visibility, the evaluation, the framing and the image attributes of nations in the news. This paper analyzed the impact of environmental issues upon nation image in the news media of four countries. Nation image is defined as the cognitive representation of a country and it is comprised of projected image (i.e. the image as an attribute of the message) and perceived image (i.e. the image as a cognitive structure formulated in the minds of the audience). A particular form of projected nation image is that in the news media. It is produced by the combined operation of (a) the international news making process, (b) the strategies of actors and (c) domestic and international events. The impact of news media upon the construction of the perceived image is related to their capacity to make particular topics (agenda setting effect) and aspects of these topics (framing effect) more accessible to their audience. Quantitative content analysis was employed. The time frame of the analysis was a period of one month (June 2012, chosen because it was environmentally unremarkable) and covered the press of Greece, Turkey, Cyprus and the United Kingdom (UK). Two newspapers (of opposing political predisposition) from each country were examined and a total of 105 news articles that were published in these newspapers and focused on environmental issues in reference to another country, were content analyzed. 293 depictions of foreign countries were documented in these articles. The formation of each nation image was examined as part of the dialectic between international events and local angles. The comparative intercultural analysis allows the examination of the impact of media ethnocentrism and the operation of the nation frame. Almost all articles were placed in internal pages of the newspapers and two thirds of them were smaller than a quarter of a page. Articles occupied a statistically significant different number of pages in each country with more space given in UK and Greek newspapers. Conservative newspapers appeared to devote smaller space to environmental issues although this difference was marginally not statistically significant. Most articles were based on own newspaper sources. The difference in the mix of reporting versus opinion articles was statistically significant among countries with the UK having more editorials. Article tone also differed (in a statistically significant way) among countries: event dynamics appeared more prevalent in the UK; in Greece, event dynamics with articles sources shared importance almost exclusively, demoting the importance of the author; in Cyprus, articles sources led in importance, followed by event dynamics. Two step clustering (in order to accommodate all variable types) of news items, showed that clustering schemes are largely determined by categorical variables such as the tone of the article. References to other countries covered many areas of the world with Europe, North and South America being more prevalent. The United States of America (13% of all references to a foreign country), Brazil (6.5%), China (5.1%), France and Germany (with 4.8% each) and the UK and Spain (with 3.4% each) were the countries which most often referred to. In most articles, the country referred to was neither mentioned in the title nor the central topic of the article.


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The focus of the article was split between the domestic area of the foreign country and its operation at the level of the state system (international dimension) and was mostly unrelated to the article origin country. The effects of environmental news upon the nation image were examined at four levels: visibility, valence (evaluation), framing, and domestication of foreign nation. In terms of valence, environmental issues resulted to a neutral (-0.02) evaluation for the foreign country (on a scale ranging from -2 representing very negative to +2 representing very positive). Noteworthy is the negative valence of environmental news for the USA (-0.33; number or references or n=39) Spain (-0.30; n=10) and Japan (-0,62; n=8) and the positive valence for Australia (+0.30; n=10) and Brazil (+0,11; n=19) as well as the fact that China had a neutral rather than negative evaluation (0.00; n=15). Most references make no links to the European Union and were not presented in a conflictual frame. Notable also is the lack of presentation of a foreign country in terms of the problem it experiences due to the environment. Interestingly, one third of references were presented in terms of a strategy frame. Future works could research specific topics such as climate change and examine their presence in the public discourse at this time of a global financial crisis as well as examine the impact of environmental issues upon nation image in conditions of crisis.

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A robust extension of the MUSA method based on desired properties of the collective preference system E. Grigoroudis* (1), Y. Politis (2) (1) School of Production Engineering and Management, Technical University of Crete University Campus, Kounoupidiana, GR73100 Chania, Greece e-mail: [email protected] (2) School of Science and Technology, Hellenic Open University Parodos Aristotelous 18, GR26 335, Patra, Greece, e-mail: [email protected] * email of corresponding author: [email protected] Abstract The MUSA method is a collective preference disaggregation approach following the main principles of ordinal regression analysis under constraints using linear programming techniques. The method has been developed in order to measure and analyze customer satisfaction and it is used for the assessment of a set of marginal satisfaction functions in such a way that the global satisfaction criterion becomes as consistent as possible with customer’s judgments. Thus, the main objective of the method is to assess collective global and marginal value functions by aggregating individual judgments. This study presents an extension of the MUSA method based on desired properties of the inferred preference system. In particular, the linear programming formulation of the method gives the ability to consider additional constraints regarding special properties of the assessed model variables. One of the most interesting extensions concerns additional properties for the assessed average indices. These indices refer to the average satisfaction indices, which are the mean value of the global and marginal value functions and can be considered as the basic performance norms and the average demanding indices, which indicate customers’ demanding level and represent the average deviation of the estimated value functions from a “normal” (linear) function. The main aim of the study is to show how incorporating these additional constraints in the linear program of the original MUSA method, the robustness of the estimated results may be improved. In addition, the study presents potential problems in the aforementioned approach, especially in case of inconsistencies between global and partial judgments, and proposes alternative modeling techniques based on goal programming that may be used in the post-optimality analysis step of the method.



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Constructing robust efficient frontiers for portfolio selection under various future returns scenarios G. Mavrotas, P. Xidonas*, H. Doukas, J. Psarras 9 Heroon Polytechneiou Str., 15780, Athens, Greece * email of corresponding author: [email protected] Keywords: Multiobjective programming; Robust programming; Financial modeling Abstract An efficient frontier in the typical portfolio selection problem consists an illustrative way to express the tradeoffs between return and risk. Usually security returns are extracted from past data. This work is an attempt to incorporate future returns scenarios in the investment decision. For representative points of the efficient frontier, the minimax regret portfolio is calculated on the basis of the aforementioned scenarios. These points correspond to specific weight combinations. In this way, the areas of the efficient frontier that are more robust than others are identified.


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A DSS for Robustness Analysis in Stochastic UTA N. Christodoulakis, N. Tsotsolas*, H. Doukas University of Piraeus, 80, Karaoli & Dimitriou str., GR-18534 Piraeus, Greece * email of corresponding author: [email protected] Keywords: DSS, Robustness analysis, MAUT Abstract The aim of this paper is to present a DSS which provides the analysts with the necessary tools to use Stochastic UTA method and proceed with an in-depth evaluation of the robustness of the inferred additive value model. Stochastic UTA had been proposed to help the decision-maker in situations where he/she wishes to rank several actions (alternatives, proposals, strategies, projects, etc.) defined on several criteria while the performance of these actions on any criterion can be known with a certain level of uncertainty in the sense that they are characterised by a probability distribution on the variation interval of the criterion. The DSS assesses the value functions for a given ranking on a reference set of alternatives, provides information concerning the consistency between the assessed preference model and the global preference of the decision-maker and calculates actions’ values, weights and utilities providing at the same time a graphical representations of the results. One of the basic steps in all UTA type methods is the calculation of robustness measures through a post-optimality analysis process. In order to support the evaluation of the robustness of the assessed value functions the DSS encompasses a number of statistical robustness measures. One of these measures is Average Stability Index (ASI) which is the mean value of the normalized standard deviation of the estimated values (weights, utilities). Another measure, which is graphically represented, is the range of all assessed utilities. During the post-optimality analysis different heuristics approaches (MAX, MAXMIN) as well as an analytical one (Manas-Nedoma Hamiltonian search algorithm) are implemented for the calculation of multiple/near optimal solutions of the LP post-optimal polyhedron of Stochastic UTA. If the robustness measures are judged satisfactory by the analyst, the model shall be proposed to the decision-maker for application on the set of alternatives. Otherwise, the analyst shall request further information from the decision-maker and use the DSS to re-assess the additive value model. This DSS is programmed with Visual C#. We needed a programming language that could do very fast a large number of mathematical operations, with less lines of code. C# is a structured language, which permits the splitting of big programs into small classes of code. It has a lot of the characteristics of a high level language, but can also use the same programming details, like a symbolic language. C# also accomplished all of our requests concerning the graphical part of GUI application. For solving the linear programs that arise from the use of the method of Stochastic UTA, we use the lp_solve 5.5.0.14 which is an open-source LP solver. It is a very powerful tool which can solve linear programs using advanced techniques to accelerate the process of finding the initial feasible solutions. Furthermore, we developed our own LP solver and we use it for implementing the Manas-Nedoma algorithm during the post-optimal process.


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Using Robustness Analysis of Preference Models into Disaggregation - Aggregation approaches for supporting interactivity A. Spyridakos*, N. Tsotsolas, D. Yannacopoulos P. Ralli and Thivon 250, 12244, Aigaleo * email of corresponding author: [email protected] Keywords: Decision Support Systems, Robustness Analysis, Multicriteria Decision Aid Abstract Multicriteria Disaggregation – Aggregation (D-A) approaches for discrete alternative actions as they applied on UTA* and UTA II methods aim to the assessment of preference models (usually of additive value) based on Decision Makers (DMs) global preferences. Linear Programming (LP) techniques are employed in order to estimate additive value models that reproduce a ranking of the reference alternative actions as close as possible to the DM’s pre-ranking. Special post optimality techniques are employed in case of the assessment of infinitive solutions (low robustness of the preference models) in order to select a representative working solution (usually the barycenter solution). Low robustness of the assessed preference models could be the result of a low structuring of the problem formulation as well as could be a mirroring picture of what the DM has really in his/her mind. In addition, robustness features enclose useful information about the structure of preferences and cannot always be considered as a bad situation and can provide an opportunity for deeper search into the problem structuring and DM's preferences. This research work is oriented on the Robustness Analysis of the assessed preference models. New indexes and a graphics software are presented for the measurement and visualization of the preference models' robustness in a way that can support the uncovering of the nature of low robustness. The exploitation of the robustness analysis results can trigger a set of interactive feedbacks so as on the one hand to lead to the increasing of robustness and on the other to the assessment of a more consistent additive value model to the DMs' preferences. The graphics software support the presentation of high dimensional data into a 3d graphics picturing the degree of robustness of the estimated additive value models. The above mentioned approaches are illustrated through a real world example.


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Process Mining in software events of Open Source Software projects E. Kouzari*, I. Stamelos Department of Informatics Aristotle University of Thessaloniki, Ethnikis Antistaseos 16 Kalamaria Postal Code : 54124 Thessaloniki, Greece * email of corresponding author: [email protected] Keywords: Process Mining, Software Events, Open Source Software Abstract Process Mining has only been extensively studied for the past few years and yet it has already helped to better understand the way systems work and made possible the extraction of knowledge that can be used to improve processes of a system. In this paper, the focus of process mining is on Open Source Software projects and software events. The use of data that are publicly available on the web with the application of process mining algorithms can lead to useful conclusions on characteristics of successful projects and ways to help those who appear to be risky. This can be achieved by analyzing the event logs in order to extract process models but also in order to identify social networks within the community of a project. In addition, with further research and analysis a general process specification could be created to help Open Source Software projects to reengineer their processes and improve their activities in order to succeed. In this paper there is an attempt to extract a process model from a large Open Source Software project and compare it with the process that the development team should follow. More specific, the effort is focused on the bug handling process and thus, the extraction of the followed process model could help improve the way tasks are shared and bugs are closed.


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A Novel Formulation for the Integrated Quay Crane Assignment and Scheduling Problem E. Theodorou*, A. Diabat Masdar Institute of Science and Technology * email of corresponding author: [email protected] Keywords: quay crane assignment, quay crane scheduling, integration, unidirectional crane schedule, port operations Abstract Over the past decades, globalization has led to an increase in the transshipment of container goods and a corresponding increase in container terminal efficiency, as port operators aim to optimize processes and procedures in order to accommodate the increasing demand. As quay cranes constitute a significant determinant of container handling efficiency, problems such as the Quay Crane Assignment Problem (QCAP) and the Quay Crane Scheduling Problem (QCSP) have received great attention in recent research streams. The aim of the QCAP is to assign a number of cranes to incoming ships, while the purpose of the QCSP is to schedule the cranes’ tasks of unloading and loading containers. However, these interdependent problems are usually solved sequentially, due to the high complexity of their integration, leading to a potentially inefficient utilization of resources. The objective of this paper is to present a novel and simple formulation for the integrated Quay Crane Assignment and Scheduling Problem (QCASP), which does not surpass the individual problems in complexity. The purpose of the model is to provide the simultaneous assignment and scheduling of cranes and which can be solved easily and in a time-efficient manner to provide practical solutions for port operators. The methodology of constructing the model for the integrated QCASP initially consists of defining the decision variables and then creating the objective function and constraints to produce the mixed integer program (MIP). The purpose of the model is to assign cranes to ships that are berthed within a given planning horizon. Furthermore, the model specifically decides which crane is allocated to which bays and it aims to minimize the time required for the completion of the handling of the latest ship, i.e. the ship carrying the largest number of containers, which is expected to take the most time at the berth. The physical considerations as well as the assumptions for the modeling process are clearly described. Specifically, as cranes travel on a single rail alongside the quay, it is important that crane positioning constraints are imposed. The first set of these constraints refers to the non-crossing of cranes, while the second set ensures that a safety margin is maintained at all times between them to prevent crane interference. One assumption of the model is that quay cranes travel in a single direction, and this allows for the elimination of the time factor from the scheduling problem. This leads to a major decrease in computational time, as the number of decision variables is significantly lower, while the results remain practical and useful due to the consideration of important conditions. The practical implications of a model that is easily solved are of great importance for port operators, since they can provide useful insights for operations, with a simple and fast algorithm. This systematic approach is expected to increase efficiency of operations as it will outperform the traditional common practice of basing decisions on experience and perception. Results demonstrate that the model provides optimal solutions in very good computational time and significant conclusions can be drawn regarding efficient utilization of resources.


Book of Abstracts

2nd



Generation of the exact Pareto set in multi-objective traveling salesman and set covering problems K. Florios*, G. Mavrotas Laboratory of Industrial and Energy Economics, National Technical University of Athens, Zographou Campus, 15780, Athens * email of corresponding author: [email protected] Keywords: multi-objective TSP, epsilon constraint, exact Pareto set, GAMS Abstract It is well known, that the calculation of the exact set in Multi-Objective Combinatorial Optimization (MOCO) problems is one of the most computationally demanding tasks as most of the problems are NP-hard. In the present work, we use the improved version of augmented epsilon-constraint (AUGMECON2), a Multi-Objective Mathematical Programming (MOMP) method which is capable of generating the exact Pareto set in Multi-Objective Integer Programming (MOIP) problems, for producing all the Pareto optimal solutions (POS) in two popular MOCO problems: The Multi-Objective Traveling Salesman Problem (MOTSP) and the Multi-Objective Set Covering problem (MOSCP). The computational experiment is confined to bi-objective problems that are found in the literature. The performance of the algorithm is significantly better to what is already found from previous works and it goes one step further generating the exact Pareto set to till now unsolved problems. More specifically, 16 symmetric instances of MOTSP with 2 objectives and 100 cities, known from the literature, are exactly solved for first time. The instances are of various types, namely Euclidean, random matrix or mixed type of the previous two. The exact Pareto sets (EPS) are computed for all 16 instances in 24-72h wall clock time with standard hardware technology. The AUGMECON2 algorithm, coded in Fortran, uses a properly modified Branch-and-Cut-and-Heuristic (BCHTSP) model available in GAMS Model Library as a subroutine for the solution of the epsilon-constraint TSP-like sub-problems. The results show substantial differences (or improvements) to best known solutions so far (typically more POS are found than were previously known). In light of the exact Pareto sets, state-of-the-art Multi-Objective Metaheuristics (MOMHs) are evaluated. The Two-Phase-Pareto-Local-Search (2PPLS) of Lust and Teghem (2010) achieves coverage at most 50-55% of the EPS, over 20 trials, for the Euclidean instances. This percentage drops to 25% for the random matrix instance. The Best-Known solution sets of Paquete and Stützle (2009) achieve coverage at most 90% of the EPS for the Euclidean instances. This percentage drops to 35-55% for random matrix instances. Also, the Weighted Sum method, on average, calculates only 3 to 5 percent of the POS, so apparently it does not suffice. Regarding MOSCP, exact solution of instances named 201a and 201b (previously unsolved in the literature) from MOCOlib benchmarks for MOSCP by X.Gandibleux is achieved for first time. Overall, calculation of the EPS for 42 out of 44 benchmarks available has been made possible (limit 24h of computation). In conclusion, the AUGMECON2 method featuring BCHTSP is among the few exact solution methods for MOTSP and the one that solved available 100 cities bi-objective TSP problems exactly for first time. References [1] T. Lust, J. Teghem, Two-phase Pareto local search for the biobjective traveling salesman problem, Journal of Heuristics 16 (2010) 475-510. *2+ L. Paquete, T. Stützle, Design and analysis of stochastic local search for the multiobjective traveling salesman problem, Computers & Operations Research 36 (2009) 2619-2631.


Book of Abstracts

2nd



Are there low-risk trading opportunities in sport betting exchange markets? M. Ioulianou*, K. Talattinis, G. Stephanides Department of Applied Informatics, University Of Macedonia, Greece * email of corresponding author: [email protected] Keywords: Low-risk bet-trading,boolinger bands, technical analysis, bet-exchange market, trading techniques Abstract Existing literature supports the notion that weak form of efficiency is usually followed by bet-exchange and prediction markets. Consequently, low-risk trading opportunities leading to profitable investments may be identified. However, in order to exploit these opportunities, several conditions should be met. The most important issue is the immediate identification of a valid situation and the instant exploitation on the spot of that specific opportunity. Moreover, trading strategies, portfolio management and behavioral finance theories are significant and play a crucial role in the strategy proposed in this paper. This work focuses on investigatingP a large data volume and detecting patterns that offer opportunities for low-risk bet-trading, via technical analysis as it is used in financial stock markets. Our empirical study is based on bet-exchange markets, specifically in horse racing. The main instrument used in the analysis of data is the "boolinger bands" tool. Our methodology is based on the behavioral finance, which proposes psychology-based theories to explain market anomalies. Additionally, market's trend recognition has a substantial significance. The combination of the above, can help in identifying low- risk trading opportunities. As soon as an opportunity is detected, by combining all type of basic trading techniques (arbitrage, hedging, scalping, backing and laying) in most of the situations we manage to benefit a profitable investment. Certainly, in order to succeed long-term profitable investments, we adopted a very cautious strategy based on portfolio management. Our results reveal that before a single game starts there could be a priori identified patterns which can lead to secure profitable investing opportunities. Through, our empirical study we notice encouraging results that show positive return of investment. These results could be optimized by using numerous other techniques, such as dynamic programming, which may introduce a more sophisticated model.

Book of Abstracts

2nd



Value focused pharmaceutical strategy determination with multicriteria decision analysis techniques K. Mastorakis* (1), E. Siskos (2), Y. Siskos (1) (1) University of Piraeus, Department of Informatics, Karaoli & Dimitriou 80, 18534 Piraeus, Greece. (2) Decision Support Systems Laboratory, School of Electrical & Computer Engineering, National Technical University of Athens. * email of corresponding author: [email protected] Keywords: Multiple criteria decision analysis, Pharmaceutical market strategy, Ordinal regression, Robustness analysis Abstract The size of the pharmaceutical market and its contribution, both in national and global level, to the regional, national and international economic development is widely recognized. This fact signifies that the supported and efficient decision making in the sector is a matter of paramount importance. This paper refers to a multicriteria assessment system for portfolio optimization in the Hellenic pharmaceutical market. The evaluation criteria are extracted from three points of view, namely: i) current market situation, ii) development of the sector over the recent years, and iii) comparison with the other Eastern European countries. The overall objective of this research work is the assessment and ranking of 192 therapeutic categories for investment purposes in the Hellenic pharmaceutical market. The ranking of these categories is obtained through the utilization of an additive value model which is assessed by the ordinal regression method UTASTAR, implemented in three phases. In the first phase, the decision maker (DM) is asked to rank a sample of these alternatives, to infer an additive value system which should be as close as possible to the DM’s ranking and as robust as possible. In a second phase, all the alternatives are evaluated and a complete ranking is obtained. Finally, in order to analyze the robustness of the model, given the incomplete determination of inter-criteria model parameters, a random weighting sampling technique is utilized, to obtain the probability that an alternative maintains its initial position in the ranking.


Book of Abstracts

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Using process mining techniques for the analysis of the processes of an emergency department in different periods of time P. Delias (1), P. Manolitzas* (2), E. Grigoroudis (2), N. Matsatsinis (2) (1) Kavala Institute of Technology, Greece (2) Decision support systems laboratory, Technical University of Crete * email of corresponding author: [email protected] Keywords: process mining, emergency department, health services, health care management Abstract The most common characteristic of an emergency department is overcrowding. Many approaches, from the area of management and information technology, have been adopted by the health care organizations in order to optimize their efficiency and effectiveness. A new approach for the optimization of the health care services is the use of process mining. Process mining research includes automated process discovery (extracting process models from an event log), conformance checking (monitoring deviations by comparing model and log), social network and organizational mining, automated construction of simulation models, model extension and repair, case prediction, and history-based recommendations. The focus of this study is to reveal the problems of emergency department using process mining techniques. The complexity and the diversity of the health care services become apparent through process mining techniques, while eventually effective visualizations provide a way to deal with. In order to develop business plans for the emergency department according to seasonality, two different data sets from different periods are analyzed. Therefore, critical parameters of the process, like the productivity of the emergency department, the bottleneck points, or the sequencing of activities are examined under the seasonality dimension as well. The analysis shows that process mining have the ability from one hand to reveal the real processes and from the other to analyse in depth the productivity of the emergency department. Furthermore the CEO of the hospital using this approach has the advantage to adjust the emergency department business plan according to seasonality parameters.


Book of Abstracts

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MEDUTA: Integrating Simulation Modeling and Multiple Criteria Analysis To Improve Emergency Department Performance P. Manolitzas* (1), E. Grigoroudis (1), N. Matsatsinis (1), N. Christodoulakis (2) (1) Decision Support Systems Laboratory, Technical University of Crete (2) Department of Informatics, University of Piraeus * email of corresponding author: [email protected] Keywords: emergency department, simulation, decision support systems, health services research Abstract The economic crisis and the austerity measures forced the governments in Europe to redesign the health care services. Furthermore, the scope of the redesign of the health care services is to minimize the human resources and the operational costs of the hospital. Emergency departments due to the economic crisis have to work under a limited number of personnel and budget. The aim of this paper is to present a novel integrated methodology in order to optimize the health care services of an emergency department. MEDUTA combines simulation techniques and multiple criteria analysis in order to improve the performance of an emergency department. In particular, using the SIMUL8 software, the operation of an emergency department is modeled and the bottlenecks of each procedure are analyzed. Based on the simulating results, the hospital management has the ability to implement alternative scenarios in order to evaluate the reaction of the system, i.e., measure the performance of the emergency department. Furthermore, in order to enhance the decision process we use the stochastic UTA model, which is a regression based approach adopting the aggregation-disaggregation principles. The main aim of the disaggregation approaches is to analyse the behaviour and the cognitive style of the Decision Maker (DM), i.e., the director of the emergency department. Thus, the model is able to improve the DM’s knowledge about the decision situation and his/her preference that entails a consistent decision to be achieved. In order to illustrate the applicability of the model in a real-world application, data related with the health care service processes from the emergency department of the General Hospital of Chania (Greece) were collected. We developed alternative scenarios using the simulation model that has been developed. These scenarios are focused on different number of emergency department staff, as well as the implementation of a fast track unit. The simulation results revealed that the best solution is the implementation of a fast track unit only for the ‘green’ incidences. Moreover, the results of the stochastic UTA model showed that the most important characteristics for the management of the emergency department are the criteria of the total length of stay and the waiting times. MEDUTA seems to be an effective approach for modelling decision making processes and improving health care services.


Book of Abstracts

2nd



Facilitating hospital department behavioral analysis using soft computing techniques E. Protopapadakis, P. Manolitzas*, A. Doulamis, E. Grigoroudis, N. Matsatsinis Decision support systems laboratory, Technical University of Crete * email of corresponding author: [email protected] Keywords: artificial neural networks, emergency department, health care management Abstract Simulation Techniques in health care facilities are beneficial for the optimization of the health care services, leading to better patients’ treatment and satisfaction. In this paper a combination of state of art techniques is used to forecast the end time of each treatment stage, during the patient stay at the wards of the emergency department. The core of the system is based on a self-correcting mechanism which exploits quintile functions, similarity criteria rules and artificial neural networks. Initial forecasts are made using inverse transformation for each treatment stage, providing an initial remaining time duration. Depending on the available information (entrance time, triage, doctor availability, etc.) a similarity mechanism is activated to improve the forecasted time by using the n closest observations and appropriate averaging functions. Neural networks are also used, by further refining the forecasted time using all the available information as input. The proposed methodology has been evaluated using real life data from emergency department, Chania pubic hospital, Crete, Greece.


Book of Abstracts

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The “Setting Up Young Farmers” measure and its environmental impacts on rural areas T. Bournaris*, C. Moulogianni, F. Kiomourtzi, B. Manos Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece * email of corresponding author: [email protected] Keywords: Multicriteria Analysis, Young Farmers, Fertilizers use, environmental impacts Abstract The excessive use of agricultural fertilizers damages human health and the environment. On the other hand, the “Setting up Young Farmers” measure of the Agricultural Development Plan supports the entry of young persons into the agriculture sector. This measure helps the participating young farmers in achieving maximum efficiency, using methods and environmentally friendly practices, by altering their farm plans. This study tries to assess the direct and indirect, environmental impacts of the “Setting up Young Farmers” and specifically the impacts of the fertilizers use. The analysis was made in the region of Central Macedonia in Greece among young farmers who have participated in the “Setting up Young Farmers” measure during 2007-2010. The analysis includes the implementation of an MCDA model for the farm plans optimization and the comparison of selected environmental indicators with those of the existent situation.


Book of Abstracts

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The multiplicity of goals in tree-cultivating farms in Greece P. Karanikolas, S. Rozakis, D. Kremmydas* Department of Agricultural Economics, Agricultural University of Athens * email of corresponding author: [email protected] Keywords: Farmers’ objectives, goal programming, satisficing, bounded rationality, Argolida, Greece Abstract The aim of this study is the elicitation of farmers’ goals through a multi-criteria weighted programming model. We adopt a non-interactive mathematical programming methodology that has been proposed by Sumpsi et al. (1996) and has been further elaborated by Amador et al. (1998). The weights of the various components of the utility function of the composite entity family farm/farm household of various alternative objectives are calculated. The method is implemented in the area of Ancient Epidaurus (Peloponnesus), where farming systems comprise various combinations of tree crops, such as olive-, orange- and mandarin- groves. The analysis is carried out for 70 farms, whose members have a multiplicity of on- and off- farm employment opportunities. Various alternative objectives are considered, like Maximization of Net Family Labor Income for on and off‐farm activity, Maximization of Net Farm Profit, Minimization of Farm Variable Costs, etc. Research findings indicate that farms with tree crops aim at the achievement of multiple goals. Minimization of variable expenses and attainment of a living standard are prioritized as the most important ones. The identification of sets of hierarchical goals for different types of farms/households goes beyond the conventional‐simplistic hypothesis of profit maximization in all different farm entities, pointing towards a satisficing behavior.


Book of Abstracts

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From Data Envelopment Analysis to Multicriteria Decision Support: Application to Agricultural Units Evaluation in Greece A. Valiakos*, Y. Siskos University of Piraeus, Department of Informatics, 80, Karaoli & Dimitriou Street, GR-18534 Piraeus, Greece * email of corresponding author: [email protected] Keywords: Multicriteria analysis, Data Envelopment Analysis, Ordinal regression, Robustness, Agricultural management Abstract Data envelopment analysis (DEA) is a nonparametric method in operational research and economics for the estimation of production efficiency frontiers. DEA requires general production and distribution assumptions only. However, if these assumptions are too weak, efficiency levels may be systematically underestimated in small samples. In this paper a multicriteria additive value model is proposed based on a consistent family of criteria composed be DEA’s input and output criteria. A real world case study is also conducted dealing with the evaluation of agricultural units in Greece in the frame of the European Common Agricultural Policy (CAP). CAP is set and reformed in the frame of providing producers in primary sector via a single payment schema as a direct funding based on the land area, where farmers obtain ‘entitlements’. The total production and/or the total area are taken into account to the financial aid as form of direct payment. However, since the production is no longer part of the evaluation so called sofa-farmers are financially aided. The goal of this study is to propose a support methodology to financial aid as reward, towards 2013-2020 reform of the policy. Industrial tomato production is described and the method is used as a tool for assessing global values. Production of industrial tomato in Greece is observed and analyzed which consists of approximately four hundred farmers. The UTA ordinal regression approach is proposed in order to assess a set of additive value functions. The preference information used in UTA method is given in the form of a partial pre-order on a subset of farmers (reference set). The most representative additive value function is proposed to be taken into consideration in order to financially aid the productive farmers. In order to obtain robust conclusions from the ordinal regression approach, the extreme ranking analysis method is applied, examining each farmer’s best and worst possible ranking position. Finally a suggestion is proposed towards the new policy, granting the production based approach more effective and more objectively allocating the direct payments.


Book of Abstracts

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Revenue Management of Perishable Products with Dual Sourcing and Emergency Orders C. Keramydas*, N. Tsolakis, D. Vlachos, E. Iakovou Department of Mechanical Engineering, Aristotle University of Thessaloniki, University Campus, P.O. Box 461, 54124, Thessaloniki, Greece * email of corresponding author: [email protected] Keywords: Agrifood supply chain management, perishable products, consumers’ preferences, product substitution, inventory management, revenue management Abstract The rapid increase of the global population along with the geographical expansion of agrifood distribution channels highlight the unique challenges and the increasing significance of the agrifood supply chain management, especially for perishable agrifood products. Additionally, the short life-cycle of agricultural commodities further promotes the segmentation of the food market according to prevalent pricing schemas, which are usually related to the quality level (freshness) of the traded produce. To that effect, grocery retailers often implement complex replenishment policies for fresh produce that may include alternative replenishment sources in order to maximize their revenues and profits. In this paper, we study ordering strategies for a perishable product, the price of which is related to its freshness, and thus it is decreasing over time. Apart from a regular supply channel, the retailer has the option to use a more expensive emergency one to boost revenues when the products from the regular channel are deteriorated at a level that renders then inappropriate for consumption. In this context, we also consider consumers’ preferences, and more specifically we assume that customers prefer to purchase fresh products at a premium price, while, in case of a fresh product stock-out, they are willing to buy inferior-quality products at a lower price in an ‘old-to-new’ upwards substitution mode. A profit maximization model (revenue management) is developed to determine the optimal regular and emergency quantities to be procured. Assuming a newsvendor type analysis, we provide an analytic expression for the expected total system profit and closed form expressions for the optimal (regular and emergency) ordering quantities. Based on numerical experimentation, we demonstrate that emergency replenishments may have, under certain conditions, a pivotal role in total system revenue by increasing the system’s expected total profit. Additional sensitivity analyses demonstrate the significant effect of market price, procurement cost, and lost sales cost of fresh and deteriorated products on profits, and the corresponding procurement policies. Finally, a threshold for shifting from single sourcing to dual sourcing policies is indicated in each case.


Book of Abstracts

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Use of Bi-Hyperbolic Activation Function to Optimize the Performance of Artificial Neural Networks G. Miguez*, A. E. Xavier, N. Maculan COPPE / PESC, Universidade Federal do Rio de Janeiro, Brazil, Rua Mariz e Barros, 652/502, 20270-002, Rio de Janeiro, RJ, Brazil * email of corresponding author: [email protected] Keywords: Neural Networks, Backpropagation Algorithm, Bi-hyperbolic function, nondiferrentiable optimization Abstract Artificial Neural Networks have been increasingly used for a large group of applications, including pattern recognition and signal processing. The most used model is known as Multilayer Perceptrons. Such a wide range of applications demands an efficient training algorithm and, according to the literature, the Backpropagation algorithm is the most recurrent. It is computationally efficient for training Multilayer Perceptrons networks and has solved the problem of backward propagation of the error for these networks. Some problems are still found in the use of this algorithm which limits an ampler application. Usually it takes a long time to process, even when it successfully reaches its goal of keeping the error in a desired range. This slower processing time prevents its use in many practical applications. To allow a broader use, many techniques were discussed to speed up its performance and, one of the factors believed to be responsible for slowing this process, is the activation function imbedded in the neurons of the network. This happens because of the iterative nature of the network learning process. A slower to calculate function slows down the processes involved. Another reason for this may be the saturation of the activation function used in the hidden and output layers. When the saturation of a unit occurs, the descending gradient takes very small values, even when the output error is still high. The activation or transfer function is one of the most important components of the artificial neuron. Its aim is to limit the valid range of the neuron output signal to a finite value and, usually, this range is normalized to the closed interval [0, 1]. The use of a sigmoid function is recommended since the early researches on backpropagation and neural learning and, since then a series of sigmoid-type functions have been used. An important point to be considered when using a sigmoid function is the saturation phenomena. It happens when, for a given set of inputs, the output is approximately equal to its asymptotic limits. The occurrence of this saturation during the training phase of an ANN can significantly slow down learning due to a very flat error surface. In our work we propose a new activation function, the Bi-hyperbolic function, which is compared with the traditionally used Logistic function. Tests using problems of the literature, showed a greater generalization capacity, faster convergence, higher computational speed and the use a leaner structure.


Book of Abstracts

2nd



Personalized outdoor routing: Route planning techniques and algorithms K. K. Diareme*, T. Tsiligiridis Informatics Laboratory Department of Agricultural Economy and Development School of Food, Biotechnolgy and Development Agricultural University of Athens 75 Iera Odos, 11855 Athens, Greece * email of corresponding author: [email protected] Keywords: Personalized Routing, POI, Team Orienteering Problem with Time Windows, local search algorithms Abstract Personalized routing for the tourist agenda is looking for a set of control points, usually referred as Points of Interest (POIs) to be visited, so that the total score, benefit or profit is maximized subject to a constraint on the total travel cost or time. A score or profit is associated to each POI, and for each pair of POIs a travel cost is specified. The corresponding tourist planning problem basically coincides with the Team Orienteering Problem with Time Windows (TOPTW) constraints, which is NP-hard problem that arises in vehicle routing and production scheduling framework. Personalize routing aims not only at planning an optimal route, by means of route generation and customization, but also facilitates each user by personalizing their recommendations. Although problems in this category present enormous difficulty to complete search algorithms, various heuristics and local search algorithms, found in the literature, can be applied to create a personalized route especially designed for tourists. Furthermore as a bases to future work an algorithm that solves the OP is presented where the tourist departs from a specified but not fixed point (origin) and returns to it. The algorithm uses TOP methodology to construct an initial route and then OP in order to enhance it and produce an optimal one. After the construction of the initial route heuristics, greedy local search algorithms as well as optimization techniques are implemented in order to optimize the result. Throughout the design of the algorithm consideration was taken upon future extension where starting and ending points would be different and the algorithm should produce as a result more than one optimal routes in order to facilitate not one single tourist/team but several groups. The proposed method is applied in three well known data sets, taken from the literature and is compared to four previously published algorithms. The algorithm proposed in this paper proved to be able to give similar results with previously published algorithms in acceptable computing time, and in some instances outperform them.


Book of Abstracts

2nd



Evolutionary Algorithms for Solving Resource Availability Optimization Problems related to Client Service of Different Priority Classes N. S. Thomaidis*, C. Salagaras, V. Vassiliadis, V.P. Koutras, A.N. Platis, G. Dounias Informatics Laboratory Department of Agricultural Economy and Development School of Food, Biotechnolgy and Development Agricultural University of Athens 75 Iera Odos, 11855 Athens, Greece * email of corresponding author: [email protected] Keywords: Personalized Routing, POI, Team Orienteering Problem with Time Windows, local search algorithms Abstract Personalized routing for the tourist agenda is looking for a set of control points, usually referred as Points of Interest (POIs) to be visited, so that the total score, benefit or profit is maximized subject to a constraint on the total travel cost or time. A score or profit is associated to each POI, and for each pair of POIs a travel cost is specified. The corresponding tourist planning problem basically coincides with the Team Orienteering Problem with Time Windows (TOPTW) constraints, which is NP-hard problem that arises in vehicle routing and production scheduling framework. Personalize routing aims not only at planning an optimal route, by means of route generation and customization, but also facilitates each user by personalizing their recommendations. Although problems in this category present enormous difficulty to complete search algorithms, various heuristics and local search algorithms, found in the literature, can be applied to create a personalized route especially designed for tourists. Furthermore as a bases to future work an algorithm that solves the OP is presented where the tourist departs from a specified but not fixed point (origin) and returns to it. The algorithm uses TOP methodology to construct an initial route and then OP in order to enhance it and produce an optimal one. After the construction of the initial route heuristics, greedy local search algorithms as well as optimization techniques are implemented in order to optimize the result. Throughout the design of the algorithm consideration was taken upon future extension where starting and ending points would be different and the algorithm should produce as a result more than one optimal routes in order to facilitate not one single tourist/team but several groups. The proposed method is applied in three well known data sets, taken from the literature and is compared to four previously published algorithms. The algorithm proposed in this paper proved to be able to give similar results with previously published algorithms in acceptable computing time, and in some instances outperform them.


Book of Abstracts

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Ant colony optimization in multi-project multi-mode resource constrained project scheduling M. Dermitzakis, E. Rokou*, K. Kirytopoulos National Technical University of Athens, School of Mechanical Engineering, Sector of Industrial Management and Operations Research, Heroon Politechniou 9, Zografou * email of corresponding author: [email protected] Keywords: Ant colony optimization, multi project scheduling, multi mode scheduling Abstract An evolutionary algorithm for the multi-project, multi-mode resource constrained project scheduling (M-RCPSP), based on the combination of ant colony optimization (ACO) and genetic algorithm (GA), is proposed. The problem setting consists of several parallel projects and a number of shared resource pools containing renewable and non-renewable resources. All the resources are supplied limitedly. The projects can be independent with each other or not. Each project has a number of activities that can be executed in one or more modes (multi-mode) where each mode corresponds to different resource type and amount requirements and leads to different activity duration. The common method about the multi-project scheduling problem is converting the multiple projects problem into a single project problem through the merger of a number of network plans. This method can lead to cumbersome networks that their solution can be very time consuming. In this paper a new method based on the combination of ant colony optimization (ACO) and genetic algorithm is proposed. The process is differentiated based on the existence of relations between one or more activities of a project with the activities of one or more other projects or not. This way two project sets are generated, a set of independent projects and a set of projects with outer dependencies. The set of projects with outer dependencies is divided in subsets based on the number of outer dependencies in order to form two or three subsets: of low, medium and high dependency. The projects are then ordered and scheduled based on the set that they belong. This way, all the projects that belong to the high dependency set and have higher resource requirements will be prioritized and scheduled up front, then those that still have high degree of outer dependencies but low resource requirements and so on. The scheduling process uses an adapted ACO algorithm for the M-RCPSP scheduling and the genetic algorithm handles the scheduling order and therefore the prioritization of the sets and the randomization of the projects in the same set. The multi-mode PSP Lib data sets were combined to give a variety of multi-project data sets and used to prove the efficiency and effectiveness of the proposed approach.


Book of Abstracts

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Analysis of an integrated three-echelon supply chain with stochastic demand, continuous review policies, lost sales and two-phase Coxian replenishment times M. Vidalis (1), C. Papadopoulos* (2), V. Vrisagotis (1) (1) Dept. of Business Administration, University of the Aegean, Chios Island, Greece. (2) Department of Economics, Aristotle University of Thessaloniki, Greece. * email of corresponding author: [email protected] Keywords: Three-Echelon Supply Chains, Performance Measures, Markov Analysis, Lost Sales, Continuous Review Inventory Policy, Coxian-2 Distribution. Abstract Integrating the supply chain is quite difficult because of its dynamics and the conflicting objectives employed by different facilities and partners. However in today’s competitive markets most companies are forced to integrate their supply chain. Our study focuses on a dynamic system and specifically on a supply chain with three members: a retailer, a supplier and a manufacturer. The retailer and the supplier adopt continuous review (Si,si) i=1,2, policies while the manufacturer has the capacity to fulfil any order that may be placed. The external demand process by the customers is assumed to be Poisson with average rate λ. All demands that occur during stock-outs are lost. The lead or replenishment time, L, defined as the active processing and delivery time of an order is stochastic and is assumed to follow the Coxian-2 distribution that exhibits the flexibility to model any general distribution G by matching the first three moments. Coxian distributions have been popular with modelers because their states (or groups of states) can sometimes be given a physical interpretation. The effectiveness of the system, is a function of the parameters: a) Si i=1,2 (the maximum inventory levels), b) si i=1,2 (the reorder points), c) the demand rate λ and d) the replenishment time characteristics (μ11, μ12, d11, d12, μ21, μ22, d21, d22). The main objective of this paper is to express the customer service level, i.e., the fill rate, FR, and other performance measures, such as the average inventory, WIP, and the average flow time or cycle time, CT, as functions of key system characteristics. The system is modelled as a continuous time Markov process with discrete state space. The structure of the transition matrices of these specific systems is examined and a computational algorithm is developed to generate them for different values of system characteristics. The proposed algorithm allows the calculation of performance measures –fill rate, cycle times, average inventory (WIP) – from the derivation of the steady state probabilities. The proposed algorithm can be used as an evaluative or descriptive model. Evaluative models assume a given set of input data and decision variables of the system under study and subsequently the performance measure(s) of the system are evaluated. Generative or optimization models have as their basic purpose the determination of an optimal solution to the system parameters given an overall system structure and an objective function to be optimized. Generally, generative models use evaluative models in order to compute the value of the objective function for a given set of inputs and then search for an optimal configuration. There is a great potential for a synergistic relationship between these two types. This synergy allows one to find the optimal values of inventory policies (Si, si) that serve better the external customer demand under given environmental constraints (λ, μ11, μ12, d11, d12, μ21, μ22, d21, d22).


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Centralized vs decentralized decomposition of supply chain using bi-level schema E. Kostarelou, G. K. D. Saharidis, G. Liberopoulos, D. Pandelis Department of Mechanical Engineering, University of Thessaly, Leof. Athinon, Pedion Areos, Volos 38334, Greece Keywords: Supply chain management, centralized strategy, decentralized strategy, bi-level programming, qualitative analysis Abstract In supply chain management, a good planning must be beneficial for the whole supply chain and for each participating company. However in practice, each company tends to optimize its own production unit and the centralized strategy in most cases cannot be applied. For these reasons, qualitative and quantitative analysis of the comparison of centralized and decentralized strategies is important. In serial supply chains with one factory at every level, the transportation of products and information between two stages is rather simple. When the centralized optimization cannot be applied, the decentralized strategy can be used, which leads to a different plan. The decentralized case in serial systems can be applied when the supply chain is decomposed into parts. As a result, each factory can optimize its production plan separately, with no attention to the whole chain. When the supply chain becomes more complicated many difficulties arise. One of the major problems which is hard to solve is the decision on decomposing the system. We study a system with two stages in parallel, where each stage consists of more than one factories. Every factory of a stage will supply all next-stage factories with semi-products. The problem was solved for the deterministic case. An important decision is the decomposition point in decentralized strategy. With no information among partners and without taking into consideration the plans of the same stage factories, one cannot optimize the plan of each factory separately. In general, supply chain planning problems inherently exhibit multi-level decision network structures. Such structures can be mathematically represented using multi-level mathematical programming principles. Given this behavior, the problem under consideration in the decentralized policy is formulated as a bi-level programming problem. As a result, we overcome the difficulties arisen by the competitive environment and the need for sharing full information among partners. In bi-level problems, partial information among partners is needed, while collaboration among players is not required. In order to solve the resulting linear bi-level problem, the lower level problem is replaced by its KKT optimality conditions, and the outcome of computational experiments for both local and global strategy has been compared. The results of the comparison determine the conditions under which the two strategies provide the same optimal solution for each problem bypassing the two analyses. Moreover, we conclude that the decentralized planning results in loss of efficiency with respect to the centralized planning. An interesting issue in bi-level problems is the existence of an equilibrium solution. If a solution of this type exists, the outcome is close enough to the solution of global optimization, and in some cases the outcome is identical to that of global case.

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Maximization of customer service level through variability reduction in Six Sigma supply chains D. P. Karakari, C. Papadopoulos* Department of Economics, Aristotle University of Thessaloniki, Greece. * email of corresponding author: [email protected] Keywords: Maximization of Customer Service Level, Variability Reduction, Six-Sigma Supply Chains, Literature Review, Simulation Model. Abstract Variability reduction in supply chains, especially in the context of inventory optimization and delivery performance, is the topic of several research papers. When demand is stochastic, lead time, especially, becomes an important issue and its control leads to many benefits. Shorter lead time reduces the safety stock and the loss caused by stock-out and also enhances supply chain quick response to customer requirements, all of which contribute to help companies gain and maintain competitive advantage in existing and new markets. However, the existing models in literature consider either the availability of product to the customer as a criterion for customer service level (CSL) or probability of delivering the product to the customer within a window as a measure of CSL. Away from these classical measurements of CSLs in the inventory optimization problem, we use the notion of six sigma quality for the end-to-end delivery process and apply a different approach for CSL, namely accuracy and precision of deliveries, which is the primary objective of any modern supply chain. This work constitutes an extension of the methodology proposed by Garg (2004) who uses key ideas and notions in the area of statistical design tolerancing in achieving variability reduction and synchronization in the supply chain process, leading to quicker and sharper deliveries. Given a supply chain and the mean and variance of the end-to-end lead time for a certain product-mix, the question is how to optimally distribute the pool of variance (variance pool allocation) of lead time and inventories among individual business processes so as to minimize the cost and achieve six sigma delivery performance. The latter work allows inventory to be maintained only at one stage of the supply chain and orders to be restricted to sizes of only one unit. Our goal is to extend this method and make it more practical with the objective to not only find out how variability should be allocated to the lead times of the different supply chain stages but also (i) what should be the optimal value of inventory level kept at all stages of the supply chain, (ii) without any restrictions to the size of order quantities. The key is to find out the right balance between variance reduction in lead time and increase of inventory levels at the supply chain stages so that the cost is minimized. The related literature review on the variability reduction method is presented and a simulation model is developed to verify Garg’s model as well as the proposed two extensions.


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Modeling Supply Chain Processes: A Review and Critical Evaluation of Available Reference Models S. T. Ponis*, S. P. Gayialis, I. P. Tatsiopoulos, N. A. Panayiotou, D. R. I. Stamatiou, A. Ntalla Heroon Polytechniou 9, 15780 Zografou, Greece * email of corresponding author: [email protected] Keywords: Review, Supply Chain, Modeling, Reference Models, Business Processes, SCOR, GSCF Abstract In today’s business environment, supply chains involve a number of autonomous organizations. The nature of supply chain processes with inter-organizational activities, involving different enterprises, calls for their design, analysis, control and evaluation in a well-designed and structured manner. The increasing importance of business processes inevitably puts process models, in the epicenter of the majority of the efforts for achieving the required interoperability and agility in dynamic supply chains. As a consequence, it is necessary to design new or adjusted business process models rapidly and at low cost. This can be achieved by reusing knowledge captured in reference process models. A reference model depicts structures, attributes, relationships and behaviors of objects for a given domain. It is represented in a general, reusable and applicable form, so that specific application models can be created by adaptation and modification. This paper aims to present the results of a review and initial comparative analysis of available supply chain reference models, for the particular needs of a research project*, aiming to provide a holistic approach for managing demand variability in contemporary global supply chain networks. After a short project description outlining the aims and objectives of our research, a short but detailed enough literature review on available modeling efforts is conducted. Next, an initial evaluation and screening of available commercial and academic modeling efforts is taking place, leading to the decision of turning the spotlight and focus of our research on SCOR v.10 – Supply Chain Operations Reference and GSCF – Global Supply Chain Forum reference models, as being the most compatible with the aims and particularities of our research. SCOR 10.0 has a tuple of metrics sorted in a quality related fashion, adjustable to the basic business processes of each organization, whereas, GSCF provides a standard set of business processes and guidelines for their implementation. Next, we examine and present the core concept and basic principles behind each model and compare their strengths and weaknesses under a critical and original perspective. Finally, the results of our analysis are integrated with the objectives of our research followed by a discussion on the degree of compatibility of each of the examined models with our research, leading to the selection of GSCF as the basis of development of a decision and risk enhanced supply chain reference model, focusing on demand variability management. *The research efforts described in this paper are part of the research project “A Holistic Approach for Managing Variability in Contemporary Global Supply Chain Networks” in research action: “Thales - Support of the interdisciplinary and/or inter-institutional research and innovation”, which is implemented under the Operational Programme: Education and Lifelong Learning, NSRF 2007-2013 and is co-funded by European Union (European Social Fund) and Greek Government.


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Supply chain optimization with regard to customer satisfaction: Solving with GAMS and comparing with Analytic Hierarchy Process (AHP) A. G. Bimpos, C. T. Papadopoulos* Department of Economics, Aristotle University of Thessaloniki, Greece. * email of corresponding author: [email protected] Keywords: Optimization of Supply Chains, Customer Level-Of-Service and Profit Maximization, Holding-Cost Minimization, GAMS/ AHP. Abstract During the past years much research has been devoted to the optimization of supply chains. Most of the papers were trying to find perfect models that optimize financial figures such as profit, holding cost, general costs, etc. It is well recognized by everybody that the customer is the one who gives reasons for production, transportation, warehousing and so on. In other words, he is the one who drives the whole supply chain. As a result, lately, many research studies try to optimize the supply chain operations with regard to demand satisfaction. This is also the main target of this paper, viz., the optimization of the supply chain while maintaining the customer demand satisfaction. The focus is that first we try to fulfill the demand and based on that to achieve the other targets which may be the maximization of profit, the minimization of holding and transportation cost, etc. We develop a general multi-criteria supply chain model. The supply chain consists of three main echelons before the final customer: The manufacturer, the distributors and the retailers. For each echelon there are three criteria: profit and customer satisfaction maximization and holding cost minimization. The capacity limitation of the transportation vehicles and the warehouses of each echelon are also counted. The suppliers of raw materials are also mentioned but they are just considered to calculate some parameter values of the manufacturer. The model tries to minimize the holding cost in every echelon and through this the profits are maximized while the customer satisfaction is guaranteed. Two main alternative policies to achieve these targets are presented. The first alternative proposes to hold more inventory but this leads to excess holding cost. The second alternative examines a more flexible inventory management which allows the supply chain to lower the holding cost and also to keep higher customer satisfaction. At the end, the analytic hierarchy process (AHP) is used in order to compare the proposed two alternatives. For comparison and better understanding of the AHP we introduce a third alternative which suggests keeping no inventory through the supply chain. A mathematical linear programming model is developed. To solve this model, the GAMS software package is used (edition 23.5) which solves linear, non linear and mixed integer models. The AHP and the results from the GAMS solver lead us to the second alternative as better solution. Because of the limitation of the GAMS software that we could use (demo version), some simplifications were necessary to be made. We didn’t consider the capacity of the transportation vehicles and tried to optimize the holding cost. We can’t be sure about the demand that would occur in every time period, therefore we should examine how we could cope with the demand fluctuation. The contribution of this research is the development of a general model with the main objective to fulfill the customer demand in a supply chain. The model is generic and may be further extended to various different directions.


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From “More than Moore” to “More Supply Chain”: Open Innovation Model and Funnel Project Prioritization for Supply Chains with a focus on the semiconductor industry H. Ehm*, H. Habib, A. Hansson, H. Larmon, A. Ström Am Campeon 1-12, 85579 Neubiberg * email of corresponding author: [email protected] Keywords: Semiconductor Industry, Supply Chain, Innovation, Moore's Law, Project Prioritization Model Abstract With the well known characteristics of short ramp up, long lead time and a violate market; continuous innovation is vital in the semiconductor market. Semiconductor technology is a direct enabler and a key source of productivity in downstream industries. The importance of this industry is undeniable thus it is vital that future innovation remains supported. Supply chain management is an excellent strategic tool used in this area for a fast response to constantly changing demand and in turn allows for effectively operation in a truly competitive international market over a longer period of time. This paper aims to bridge the observed gap from innovation ideas to real concrete project applications for companies. In order to construct this paper a comprehensive study was complied in a major leading European semiconductor company. Literature studies along with past master thesis projects, including both innovation topics and the semiconductor market, were utilized to gain a complete picture of the company. A new supply chain project prioritization model is constructed and discussed in this paper which uses an open innovation approach in order to envelope external trends and internal expert opinions to ensure all knowledge is gathered in the semiconductor market. The process maps high tech trends to existing roadmap projects in the company and aims to overcome the recognized bullwhip effect which causes difficulties when demand order variabilities are amplified as they move up the supply chain. This model uses two stages, scouting and ideation, and ensures projects are implemented that align with highly rated trends from supply chain, the semiconductor industry and company importance. Overall the project prioritization model allows for correct steering of a company in a truly successful direction. It can be said that this unique innovation ensures further future development of semiconductors for supply chain one can say it paved the way from Moore’s Law via “Moore than Moore” to “More Supply Chain”.


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Public Transport Priority Strategies: Progress and Prospects V. Dinopoulou (1), C. Diakaki (2), I. Papamichail (2), M. Papageorgiou (2) (1) Department of Industrial Design Engineering, T.E.I. of West Macedonia, 50100 Kozani, Greece; (2) Department of Production Engineering and Management, Technical University of Crete, University Campus, Kounoupidiana, 73100 Chania, Crete, Greece Keywords: Public transport systems; public transport priority; priority strategies Abstract In the years to come, public transport will be called to play a significant role towards achieving the sustainable transport system objective set for the future, in Europe and beyond. To this end, the quality, accessibility and reliability of its operations should be improved. In this context, the favourable treatment of public transport means within the road network may have, among others, a significant contribution. Such treatment can be derived as a result of an appropriate design of the road network facilities and/or the employed signal control at the network junctions. To this end, several approaches have been proposed, and it is the aim of this paper to review them, focusing mainly on those attempting to provide priority via appropriate adjustment, in real time, of the junction’s signal control. As far as signal control is concerned, several adjustments of the traffic lights may be adopted to provide public transport vehicles a favourable treatment at the network junctions. This favourable treatment, which is called priority, may be provided in different ways. This paper presents and discusses the levels of priority and the conditions and methods for granting priority, and classifies the relevant proposed approaches. Strategies, which have been employed in different cities all around the world are also presented and discussed, in an effort to identify the current trends and future perspectives in public transport priority systems. Based on an extensive literature review, it has been identified that, depending on the specific requirements aimed at by the provision of priority, several different signal-control based strategies have been developed and applied worldwide. A first classification distinguishes them as fixed-time versus real-time. Fixed-time strategies are in fact fixed-time signal plans, especially developed to favour the movements of public transport vehicles, while real-time strategies respond to priority requests received in real time. The real-time strategies may be further classified according to several criteria. The first criterion distinguishes real-time strategies in proactive versus reactive, depending on whether they are triggered by priority requests received well in advance from the actual arrival of the public transport vehicles at the priority junctions, or not. The second criterion distinguishes the strategies in rule-based versus optimisation-based, depending on whether their control decisions are based on a set of identified conditions or on the optimisation of an appropriately defined performance index. The relevant literature offers a few examples of fixed-time priority strategies; and numerous examples of real-time priority strategies, mainly of a reactive and rule-based nature. The same tendency is also observed in the practical applications of public transport priority systems, where the vast majority of adopted strategies include real-time, reactive, rule-based ones. Rule-based strategies are triggered by the receipt of particular priority calls and respond to them according to their underlying rules, by directly modifying the implemented signal control; this modification may be more or less aggressive, depending on the prescribed priority level. Rule-based strategies are not able to respond adequately when multiple requests arrive, simultaneously or in short time intervals, calling for contradictory signal control modifications. This limitation may be overcome by the employment of optimisation strategies. The optimisation

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strategies are, in general, able to consider in their procedures several multiple requests simultaneously,and produce signal settings that balance, as much as possible, the contradictory requirements, at the expense, however, of the required computational effort that is usually much higher than that of the rule-based approaches. For this reason, the development of more efficient rule-based strategies still remains a prime subject of research and development, which calls for novel solutions that will evidently improve the public transport operations and promote their use.

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Environmental Vehicle Routing Problem G.K.D. Saharidis*, G. Liberopoulos Department of Mechanical Engineering, University of Thessaly, Volos, 38334, Greece * email of corresponding author: [email protected] Keywords: environmental, Routing Abstract The estimation of traffic emissions has become increasingly relevant in the discussion of air quality problems, climate change and mitigation policies, due to the continued growth in vehicle use and the deterioration in driving conditions (congestion). Emission models are becoming more complex and more comprehensive with time. Modeling approaches to predict the environmental externalities (e.g. estimate CO2 emissions) coming from a move of a vehicle, are based on the estimation of fuel consumption by the vehicle. The fuel consumption is based on several factors with the most popular being distance, time, type of vehicle (e.g. body style, model year, type of engine etc.), weight load and mode of operation (e.g. different engine management concepts, gear-shift philosophies etc.). Certainly, the vehicle, which is the source of emissions, is a very important component for the evaluation and estimation of environmental externalities coming from freight transportation. However, there is also another important component which affects the amount of emissions produced by freight transportation that has been taken partially (e.g. the case of traffic by using average speed instead of real time traffic information) or not at all under consideration (e.g. the case of wind condition are not taken under consideration for the estimation of environmental externalities). This component is the characteristics of the transportation network. The transportation network is the recipient of the emissions but at the same time its specific characteristics are one of the sources of emissions (the other is the vehicle). The transportation network is composed by nodes which correspond to intersections and arcs which connect two nodes. Its arcs are characterised by many factors (from now on referred to as Transportation Network (TN) factors) which definitely influence the fuel consumption and the emission production if this arc is used. An arc of a transportation network has certain characteristics which some of them stay constant (e.g. infrastructure profile and length of an arc) and some other change dynamically in time (e.g. traffic and weather conditions). In this research, we develop a novel objective function for the environmental VRP that takes as input several data and estimates the Environmental Externalities Score (EES) of a route. This score (i.e. the EESarc) approximates the potential, for environmental externalities if this arc is used. EESarc will be estimated undependably of the fuel consumption factors like the type of vehicle, the weight load and the conditions of operation of the vehicle which is in use and depended on traffic conditions, infrastructure profile, weather conditions and length characterizing the arc under study.


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Use of SARIMA models to assess rail passenger flows: a case study of Serbian Railways M. Milenkovic (1), N. Bojovic (1), N. Glisovic (2), R. Nuhodzic (3) (1) Division for Management in Railway, Rolling stock and Traction, The Faculty of Traffic and Transport Engineering, University of Belgrade Vojvode Stepe 305, 11000 Belgrade, Serbia (2) State University of Novi Pazar Vuka Karadzica bb – 36300 Novi Pazar, Serbia (3) Railway Infrastructure of Montenegro Trg golootockih zrtava 13, 81110 Podgorica, Montenegro Vojvode Stepe 305, 11000 Belgrade, Serbia Keywords: forecasting; railway; passenger service; SARIMA Abstract Passenger flow forecasting represents a vital component for rail passenger operators which can be used to fine-tune travel behaviors, reduce passenger congestion and enhance service quality. The forecasting results of passenger flow can be applied to support rail system management such as operation planning and station passenger crowd regulation planning. In this paper, we examine the capabilities of seasonal autoregressive integrated moving average (SARIMA) models to fit and forecast rail passenger flows. We show that for given sample data, a SARIMA model could be found that adequately fitted and forecasted the time series of monthly passenger flows on Serbian railways.

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Overview of Non Linear Programming Methods Suitable for Calibration of Traffic Flow Models M. Kontorinaki* (1), I. Papamichail (1), M. Papageorgiou (1), Y. Tyrinopoulos (2), J. Chrysoulakis (2) (1) Dynamic Systems and Simulation Laboratory, Department of Production and Management Engineering, Technical University Of Crete, 73100 Chania (2) Department of Civil and Infrastructure Engineering, TEI of Athens,12210 Egaleo-Athens * email of corresponding author: [email protected] Keywords: Traffic flow, calibration, simulation, validation, optimization algorithms. Abstract The calibration procedure of a macroscopic traffic flow model aims at enabling this model to represent properly and as accurately as possible, the real traffic conditions in a motorway network. Essentially, this procedure aims to find the best values for the parameter vector of the model by exploiting the most appropriate optimization algorithm. Indeed, the non-linear, non-convex least squares optimization problem of parameter calibration is known to have multiple local minima and hence gradient-based solution algorithms are not an option. Under those circumstances, the methodologies that are more appropriate to be applied in this field are based on metaheuristic algorithms which use processes of direct search which in turn allows them to avoid local minima. In this paper, the authors present an overview of the most suitable non linear programming methods as far as the calibration procedure of macroscopic traffic flow models is concerned. More specifically, six (groups of) algorithms are described in detail, Nelder - Mead Algorithm, Pattern Search Methods, Cross Entropy Method, Genetic Algorithms, Simulated Annealing and Particle Swarm Optimization Algorithms. The procedure for calibrating and validating macroscopic models is described first, along with the description of the form of such a model as well as the corresponding performance criterion. Then, each one of the aforementioned algorithms is analyzed by presenting the general concept, describing the basic steps, discussing the usual termination criteria and listing the main advantages and disadvantages. As a matter of fact, this paper is motivated by the development of a software tool for the validation and benchmarking of traffic flow models using real data and appropriate optimization methods. The most appropriate methodologies of nonlinear programming, selected under the above considerations, are the deterministic Nelder - Mead Algorithm and the stochastic Cross Entropy Method which will be considered for implementation in the above software tool.


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Development of an objective function for the minimisation of Greenhouse Gas (GHG) emissions from in port truck operations G. E. Konstantzos*, G. K. D. Saharidis, M. Loizidou, G. Kolomvos, V. Tsoukala, M. Bourousian *National Technical University of Athens, School of Chemical Engineering, Unit of Environmental Science and Technology. 9 Iroon Polytechniou St, Zographou Campus, Athens, Greece; PC 157 73 * email of corresponding author: [email protected] Keywords: Greenhouse Gas (GHG) emissions; CO2 equivalent; emissions minimasation; port terminals; terminal operations; drayage operations Abstract Objectives The main objective of this work is the development of an objective function for the minimisation of Greenhouse Gas (GHG) emissions (expressed as CO2 equivalent) resulting from terminal and drayage operations, focusing on truck transportation and handling operations of containers (i.e. loading and unloading onto trucks). Furthermore the function is based on a holistic approach for the estimation of CO2 equivalent emissions considering all factors contributing to their increase. Methodology Firstly, a critical review of emission calculation models was performed, and their capabilities and suitability for the estimation of CO2 equivalent production from the operations during the handling and transport of containers to, from, and within marine terminals was assessed. Based on this analysis, COPERT (www.emisia.com/copert) was chosen to be used as a basis for the development of the objective function for the minimisation of GHG emissions. COPERT was selected for several reasons but mainly because its methodology balances the need for detailed emission calculations on one hand and use of few input data on the other. The next step was to analyse COPERT’s equations in depth in order to assess and evaluate their limitations. In summary, emission calculations take into account the mean speed, the type of the engine, the weight and the mileage of the truck, the load, the road gradient, the type of fuel and the travelled kilometers; however these equations do not take into consideration various attributes of port operations. In order to develop certain modifications to reflect port conditions, more case-specific variables and parameters affecting emission production were considered. Among them, were (1) stop-and-go traffic (average number of stops per unit distance), (2) stop duration (average time in idle mode) and (3) usage of air conditioning. The final step was to modify COPERT’s equations introducing specific coefficients that assess the effect of the aforementioned new variables. These coefficients were developed based on literature research and depend on a variety of variables. For instance, regarding usage of air conditioning, coefficients were calculated based on weather conditions (i.e. air temperature and humidity), while in case of stop-and-go traffic and stop duration, coefficients’ calculations were based on port infrastructure and traffic density. Finally, taking into account all the above-mentioned parameters, an objective function for the minimisation of GHG emissions from in port truck operations was developed. Further Work Future steps include the further validation of the final objective function, as well as its application for various cases.


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Simulation Analysis of a pilot handling system for the rail transport of conventional semitrailers A. Ballis* NTUA, Department of Transportation Planning and Engineering, 5, Iroon Polytechniou, GR-15773, Athens, Greece * email of corresponding author: [email protected] Keywords: Simulation, handling equipment, rail transport, semitrailers Abstract The European Intermodal transport is facilitated by use of four main freight systems: the ISO container based system, the inland container and the swap body based transport system as well as the semi-trailer based transport system. Semi-trailers are essential components of the road traffic and thus also of the pre- and post-haulage parts of the intermodal/combined transport chains. The use of semi-trailer as a loading unit in the railway transport has a long record, either as cranable semi-trailers (that are loaded on special wagons by cranes or reach stackers) or as conventional (non-cranable) semi-trailers that are loaded on trains using various horizontal handling techniques (rolling motorways, the Modalohr system or the ISU system). The system ISU (“Innovativer Sattelanhaenger Umschlag” ) was designed to allow the transport of existing (non-cranable) semi trailers by picking them from their wheels, e.g. by applying the same forces as when they are sitting-on during road transport. A prototype has been developed and demonstrated in the Wien Nordwest terminal as well as in Wells terminal in Austria. The pilot run of the system has been performed on the Austria –Turkey route as a part of activities performed within European CREAM project. In parallel effort was given to the analysis and improvement of the operations and the configuration of the ISU system aiming to develop the “next generation” of this equipment. The handling system of ISU deviates a lot from the known conventional handling operations. It consists of a number of wheel-packer elements, a transverse beam and an adapter with hoisting ropes that is mounted to a Reach Stacker spreader. The wheel-packer elements are located in a special ramp (ISU-ramp). The service cycle of ISU is largely dependent on the initial conditions (wheel grippers in ramp slots or in a wagon, reach stacker near the ramp or near the railway line, tractor waiting to attach or detach a semi-trailer) and the sequence of handling requests (loading or unloading operations). In order to analyse the above complex operating conditions a simulation based analysis has been performed by the NTUA research team participating in the CREAM project consortium. A simulation model with animation capabilities has been developed and calibrated (handling and service cycle times) using video recordings of the pilot ISU system in operation in Wells. The scope of the current presentation is to outline the methodological framework used for the above simulation analysis and the functionalities of the simulation model, as well as to present the results of the research work.


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Towards a long-term security of supply in electricity markets: Testing capacity mechanisms in an experimental setting D. Lara*, S. Arango Decision Science Department, Universidad Nacional de Colombia, Carrera 80 N. 65-223, bloque M8-211., Medellín, Colombia * email of corresponding author: [email protected] Keywords: electricity markets, capacity mechanisms, game theory, laboratory experiments Abstract Long-term security of supply is among the main current concerns in deregulated electricity markets. Many capacity mechanisms have been proposed to address this problem. In this paper we study two of them: Procurement for long-term strategic reserve contracting and Centralized auctions, using simulation and laboratory experiments. We hypothesize that both mechanisms will help to stabilize markets prices, but increase the total cost of the system. In order to compare the market effectiveness of the two mechanisms we consider the economic surplus as a measure of society’s welfare. We begin our work by setting a benchmark for the behavior of a deregulated electricity market, both with simulation and experimental results. Then we propose two experimental designs, one for each mechanism, to make simulations and laboratory experiments that can be compared with the benchmark we set. We performed four sessions of laboratory experiments, two for each mechanism in order to assess the potential to stabilize market’s prices of each capacity mechanism independently and comparatively. Both mechanisms deal with other market issues besides their potential to stabilize prices, such as their compatibility with the market principles, i.e. the capacity mechanism has to stabilize the market price without becoming a coercive force that fully determines the market operation. To deal with this concern, we ensure that both the market production capacity and the price in our experimental designs are determined by the players’ decisions. With these settings, our first results suggest that both mechanisms can stabilize the market. However, they present significant differences in their effectiveness and potential cost. Furthermore, we present some practical concerns regarding the implementation of each of the mechanisms. With this framework, we propose further research, with more sessions of experimental markets, so we could determine the stabilization potential of each mechanism more accurately and thus perform a more precise comparative analysis of them.


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The Feasibility of Renewable Energy in the Gulf Cooperation Council Countries D. N. Al-Ajmi* Geography Department, Sultan Qaboos University, Sultanate of Oman * email of corresponding author: [email protected] Keywords: Renewable, Energy, Greenhouse, Technologies Abstract The Feasibility of Renewable Energy in the Gulf Cooperation Council Countries Dhari N. Al-Ajmi Geography Department, Sultan Qaboos University, Sultanate of Oman. ABSTRACT The Intergovernmental Panel for Climate Change (IPCC) held its meeting in Abu Dhabi, United Arab Emirates, in May 2011. The IPCC through the meeting of its 11th session of Working Group 3 concluded that almost 80% of world's energy supply could be met by Renewable Energy (RE) by mid-century if backed by the right enabling policies. This will save about 220 to 560 Gt of CO2 from 2010 to 2050 and will keep the greenhouse gases concentration level to 450 ppm. The key factor for this development is falling costs of RE technologies per kWhs. This paper will give an insight of the importance of shifting into renewable energy in the Gulf Cooperation Council (GCC) countries. In addition some examples of the existing activities in this issue in the Arabian Gulf region will be presented. Kew words: Renewable Energy, greenhouse gases, technologies.


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Evaluating long term potential natural gas supply alternatives for Greece with multicriteria decision analysis S. Androulaki*, J. Psarras, D. Angelopoulos School of Electrical & Computer Engineering, National Technical University of Athens, Greece, Decision Support Systems Laboratory * email of corresponding author: [email protected] Keywords: Natural gas, Multicriteria analysis, Ordinal regression, Robustness analysis. Abstract Most of the European Union countries are fully dependent on natural gas imports, with the greater proportion of their supplies coming from Russia. In the case of Greece, the issue of security of supply is one of the most important pillars of Greek energy policy for natural gas. Events, such as the Russia-Ukraine rupture, which resulted in supply interruption of Greece with Russian natural gas for more than two weeks in January 2009, reflect the necessity of diversifying supply sources. On the other hand, the recent institutionalization of liberalization of natural gas markets throughout the European states aims to the development of flexible and competitive natural gas markets. Nevertheless, the necessity of effective long term natural gas supply strategies at national level remains crucial in terms of security of supply. This paper outlines an evaluation study of long term potential natural gas supply alternatives for the case of Greece. Alternatives to be evaluated have been defined at state and at corridor level, meaning that an alternative is described as "negotiation to contract natural gas supply produced in country X through corridor Y" with a view to negotiating for long term agreements. The paper outlines a multicriteria evaluation system based on three points of view: (1) the economics of supply (relative transfer cost, production cost); (2) the security of supply (transit countries, reserves-to-production ratio, overall risk); and (3) the cooperativity between countries (total trade, total energy trade). The overall evaluation of the available supply alternatives has been obtained by an additive value function assessed with the help of the UTA II ordinal regression method. Given the incomplete determination of weighting factors obtained through UTA methods, a robustness analysis has been conducted using the extreme ranking analysis algorithm. Within this algorithm the best and worst rank position for each individual alternative is estimated.


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The effect of Wind Power penetration on the wholesale prices in Electricity Markets A. Sietis*, D. Angelopoulos, H. Doukas, J. Psarras Decision Support System Lab, School of Electrical and Computer Engineering, National Technical University of Athens, Iroon Polytechneiou 9 Str., 157 73, Athens, Greece * email of corresponding author: [email protected] Keywords: RES-S, Merit Order Effect, Negative Prices, Support Schemes, Price Reduction Abstract Through the last decade, the Renewable Energy Source (RES) deployment has been rapidly increasing in Europe and more targets have been set regarding the penetration of Renewable Energy until 2020. Sceptics protest that the current approach of the electricity market development and RES integration is unavoidably doomed because it leads to extremely tight situations that threaten the stability of the market. This paper focuses on the investigation of the effects of wind power penetration on the wholesale prices in electricity markets. Specifically, the basic characteristics of any electricity market are demonstrated and the roles and the dynamics of the producers, the retailers, the final consumers and the TSOs are analyzed. Furthermore, the main Price Settling Mechanisms and the possible RES support schemes are presented and compared not only theoretically but also via empirical investigation of the European countries that have already implemented them. The high wind power penetration through the biggest European countries, compared to other RES, and also the special characteristics of this particular energy source (high wind intensity at night, high stochastic behavior and quick changes, safety thresholds etc) are also included in this analysis. The Merit Order Effect is explained and illustrated via both theoretical and empirical approach trying to evaluate the final total cost of the support scheme for the final consumers regarding wind production and decide eventually if it is beneficial or not from a consumers’ perspective. Moreover, Negative Electricity Prices, a phenomenon that stems from the integration of wind power, is also explained. Negative Electricity Prices first occurred in Germany at 2009 when EPEX allowed producers to bid at negative prices. The situation is analyzed, the arguments that support their existence are examined and the reasons that lead to such ambiguous and controversial situations are put under the microscope. A review of the solutions currently presented in the literature which are aiming either at a short term decompression of the problem or at long term structural changes is incorporated in this paper. Finally, suggestions are made on both issues and solutions, regarding the optimal operation of the electricity markets, compared to the existing European Markets, and also an overview of the current scientific literature about the subject is presented.


Book of Abstracts

2nd



Methodology of Forecasting Natural Gas Demand in Greece N. Z. Legaki*, S. Androulaki,V. Ntavelis, N. Mavroeidis , V. Assimakopoulos Heroon Polytechniou 9, 15780 Zografou, Greece * email of corresponding author: [email protected] Keywords: Natural gas demand, forecast, time series methods, accuracy Abstract Modern global trend, which indicates the increase of natural gas’ use, has a great influence in energy planning of Greece. Expected even greater penetration as it is the cleanest source of primary energy, after renewable sources, and that it’s price ranges lower than oil. (its)The improved performance ration in conjunction with its low carbon emissions, make natural gas an important component of Greek energy mix. The greater the introduction of natural gas in the energy balance of Greece is, the more important the forecast of its consumption becomes. Forecasting gas consumption is particularly important in the distribution companies, as in the final consumers in order to complete the business process. In this study, it is presented an integrated methodology of natural gas demand forecasting for medium and long term horizons, based on time series methods. Specifically, the methodology is consisted of several distinct steps. Firstly, analysis of daily data of gas quantity consumption is taken place such as weekly aggregation, elimination of missing values and special events and deseasonalization. Thereafter, time series models as exponential smoothing and theta model are evaluated through measuring their performance via accuracy metrics (MAE, MAPE). More accurate forecast model is selected to calculate the estimated quantity of natural gas demand. Finally, forecasts are disaggregated to daily frequency through equal weights. A wide range of daily data; from unique consumers to aggregated data of exit points of natural gas, has been examined. Better results about the accuracy of the applied methodology are obtained for aggregated data per exit point or per weekly aggregation, because of the smoothing of data time series. Finally, the effect of special days’ impact factor has been calculated and embodied, without achieving more accurate results. In conclusion, the presented methodology is integrated through an information platform system, which is friendly use and useful tool for natural gas distributors companies.


Book of Abstracts

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Optimization of medium-term natural and liquified gas supply for a Distribution Company E. Chatzithanasis*, S. Androulaki, J. Psarras Laskou 26, Psychiko, Greece * email of corresponding author: [email protected] Keywords: LNG supply, natural gas, optimization, Decision Support System Abstract The development of specialized Decision Support Systems is needed more than ever, in today’s rapidly changing world. This need is even more conspicuous in the natural gas market since the Deregulation and Pipeline Unbundling. In this newly formed environment new players may enter the market. The Liquified Natural Gas, easily transferred by ships, has impacted dramatically on the formation of the modern structure of the natural gas market . Taking into consideration these new market conditions, distribution companies have to adjust their tactical planning. Getting used to their new role, Distribution companies focus on the delivery of natural gas from the major pipelines or LNG sources, to the end user. To remain competitive and profitable Distribution companies have to optimize their supply plans based on different and complicated parameters. This paper aims to provide a managerial tool for the tactical and strategic decision making level, rather than focusing on the day to day operation. This approach meets the need for a simplified analysis of different scenarios for the higher levels in an organization’s hierarchy. We are trying to establish the most influential external variables that influence the supply cost and find the minimized yearly cost. Benefits offered by this approach for cost minimization in a variety of business scenarios, such as the case where the company can hold some amount of gas in storage, the optimized annual delivery plans, planning and optimization of all modes of transportation including pipeline, shipping and liquefaction, are studied and presented. Scenarios with different types of contracts to manage the natural gas supply, are also taken into consideration. The main purpose of this study is to develop an optimization model for the yearly annual planning of a natural gas Distribution company that holds a monopolist position in a local market. We have exploited Linear Programming with an objective function that seeks to minimize the yearly gas supply costs, using monthly decision variables. It is a tool that its main goal is to provide a general view of the company’ s options and the basic strategies that can be followed through different scenarios.


Book of Abstracts

2nd



Public Data curation with the ENGAGE platform and OpenRefine S. Mouzakitis* National Technical University of Athens School of Electrical & Computer Engineering Management & Decision Support Systems Laboratory (EPU-NTUA) 9, Iroon Polytechniou str., 157 80, Athens, Greece * email of corresponding author: [email protected] Abstract The purpose of this workshop is to demonstrate a practical and efficient workflow for Public Data curation by using the ENGAGE platform and Open Refine. The ENGAGE e‐infrastructure is envisaged to promote a highly synergetic approach to governance data research, by providing the ground for experimentation to actors from both ICT and non‐ICT related disciplines and scientific communities, as well as by ensuring that the scientific outcomes are shared among the citizens through a social collaboration environment. OpenRefine is a popular tool for preparing and cleaning data before applying computational and statistical methods. The ENGAGE e‐infrastructure is envisaged to promote a highly synergetic approach to governance research, by providing the ground for experimentation to actors from both ICT and non‐ICT related disciplines and scientific communities, as well as by ensuring that the scientific outcomes are made accessible to the citizens, so that they can monitor public service delivery and influence the decision making process. - See more at: http://www.engage-project.eu/engage/wp/?page_id=166#sthash.hYBveLOg.dpuf


Book of Abstracts

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Towards a Multicriteria Decision Support System for e-Government Benchmarking in European Union I. Matzakou*, E. Siskos, D. Askounis Decision Support Systems Laboratory, School of Electrical & Computer Engineering, National Technical University of Athens, 9, Iroon Polytechniou Str., 157 80, Athens, Greece * email of corresponding author: [email protected] Keywords: E-government benchmarking, Multicriteria analysis, Decision Support System Abstract E-government benchmarking is being conducted by various organizations but its assessment is based on a limited number of indicators and does not highlight the multidimensional nature of the electronically provided services. In this paper, we propose the design, development and implementation of a Decision Support System (DSS) to enable stakeholders achieve an e-government evaluation based on their own preferences. The proposed DSS embeds a multicriteria evaluation methodology, based on four points of view: (1) infrastructures, (2) investments, (3) e-processes, and (4) users’ attitude in order to evaluate European Union countries. In the first phase of its implementation, twenty one European Union countries are evaluated and ranked over their e-government progress. The DSS uses an additive value model which is assessed by the ordinal regression method UTA II, along with specific mathematical programming techniques, in order to evaluate and rank each country. It is designed to be launched on the World Wide Web (WWW) and therefore be available to citizens, decision makers and all relative stakeholders.


Book of Abstracts

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A Methodology for Determining the Value Generation Mechanism and the Improvement Priorities of Open Government Data Systems E. Loukis*, Y. Charalabidis, H. Alexopoulos University of Aegean, Department of Information and Communication Systems Engineering * email of corresponding author: [email protected] Abstract Many government agencies worldwide are making big investments for developing information systems that open important data they possess to the society, in order to be used for scientific, commercial and political purposes. It is therefore necessary to understand what value they create and how, and at the same time – since this is a relatively new type of information systems – to identify the main improvements they require. In this direction this paper presents a methodology for determining the value generation mechanism of open government data (OGD) systems and then priorities for their improvement. It is based on the estimation, based on users’ ratings, of a ‘value model’, which consists of several value dimensions and their corresponding value measures, organized in three ‘value layers’, and also the relations among them. These three value layers concern the efficiency of the OGD (= quality of the various capabilities it provides to the users), its effectiveness (= degree of supporting users for achieving their objectives) and also users’ future behavior intentions respectively. The proposed methodology has been applied succesfully to an advanced OGD system developed as part of the European project ENGAGE (‘An Infrastructure for Open, Linked Governmental Data Provision towards Research Communities and Citizens’), leading to interesting insights and improvement priorities. This first application provides evidence that our methodology can be a useful decision support tool for important ODG systems investment, management and improvement decisions.


Book of Abstracts

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An investigation of Open Data Infrastructures characteristics: rationale and end-user perspective P. Kokkinakos*, M. Petychakis, A. Zuiderwijk, S. Mouzakitis, E. Argyzoudis, J. Psarras Decision Support System Lab, School of Electrical and Computer Engineering, National Technical University of Athens, Iroon Polytechneiou 9 Str., 157 73, Athens, Greece * email of corresponding author: [email protected] Keywords: Open Data, Infrastructures, End-User, Needs, Stakeholders Abstract The paper at hand aims towards investigating the differentiated requirements of Open Data infrastructures from an end-user perspective and per stakeholder group. The analysis has been performed in the context of the ENGAGE FP7 e-Infrastructures Project. The first steps of the paper include extensive literature review, study of relevant use case scenarios, interviews, workshops, consultation and conversations between the ENGAGE consortium and representatives of the various end-users’ groups, as well as brainstorming amongst experts and the ENGAGE consortium. The reported results show that the end-users’ needs cover a rather wide spectrum: social/ community characteristics (e.g. integration with social channels, private messaging), uploading/ storing/ downloading features, statistical analysis/ comparing mechanisms/ integration mechanisms/ visualisations, metadata/ high level descriptions, legal disclaimers, training facilities, applications etc. A comparative cross analysis depicts the common needs of all end-users’ groups, as well as specific needs that apply only to particular stakeholders’ groups. Based on the needs recognised, suggestions towards open data infrastructures and the open data community were derived. The ENGAGE project will constitute the initial test-bed of the results of the work performed.


Book of Abstracts

2nd



Data.gov.gr Case Study T. Papadopoulos Abstract The purpose of this workshop is to present the development and operation of the Data.Gov.gr initiative from its conceptual phase until now, and debate on the expected impact and benefits for the citizens and a transparent government.

Book of Abstracts

2nd



Dealing with Robustness in Government Decision-Making using Facilitated Modelling N. Tsotsolas*, S. Alexopoulos Department of Informatics, University of Piraeus, Karaoli & Dimitriou 80, 18534 Piraeus, Greece * email of corresponding author: [email protected] Keywords: Robustness Analysis, Government Decision-Making, Facilitated Modelling, MCDA Abstract The government decision-making processes have always been a subject of philosophical enquiry and an open field for debating in OR community for the last 40 years. Nowadays, this specific topic is at the forefront of the discussion because of the crisis in Europe which emerges the urgent need for defining “efficient policy” concepts. The produced policies should be the rational and robust outcome of a collective decision-making process, based on a well-defined and sound framework of rules and methods. Policy decisions (e.g. economic, fiscal, development) are often complex and multifaceted and involve many different stakeholders with different priorities or objectives. Very often decision-makers, when confronted with such problems, attempt to use intuitive or heuristic approaches to simplify the complexity until the problem seems more manageable. In this process, important information may be lost, opposing points of view may be discarded, and elements of uncertainty may be ignored. In short, there are many reasons to expect that, on their own, individuals will often experience difficulty making informed, thoughtful choices in a complex decision-making environment involving value trade-offs and uncertainty. The problem is even more complex if we consider that, according to principles of sociotechnical design, specific - most of the times conflicting - objectives shall be best met by the joint optimization of technical and social aspects. Of course, the absence of certainty and the presence of complexity shall not be an excuse to do nothing. The well-known area of Multi-criteria Decision Aiding (MCDA) offers techniques designed to deal with situations, as the aforementioned, in which there are multiple conflicting goals. Furthermore, the process of creating, evaluating and implementing strategic political decisions is typically characterised by the consideration of high levels of potential synergies between different options, long term consequences, and the need of key stakeholders to engage in significant psychological and social negotiation about the strategic decision under consideration. MCDA can efficiently tackle all these issues. However, the political decision and negotiation process among members of the governmental committees does not take place in a political vacuum and political conflict is a reality. Thus, certain adaptations to the methods, tools and processes of MCDA are required if it is to be effectively applied in such a context. As already mentioned, a crucial issue, when dealing with political decisions, is the radical uncertainty about the present (e.g. lack or poor quality of information) and also about the future. The latter one addresses the seeming paradox - how can we be rational in taking decisions today if the most important fact that we know about future conditions is that they are unknowable? Robustness Analysis is a way of supporting government decision making when dealing with uncertainties and ignorance. In the present research we discuss the different definitions and approaches of Robustness Analysis in government decision-making concerning the present (robust solutions, robust methods, robust processes and robust conclusions) and the future (initial commitments, ‘futures’ and possible configurations). We also initiate the discussion concerning the application of Robustness Analysis as a way to


Book of Abstracts

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support the identification of potential robust strategies, characterize the vulnerabilities of such strategies and evaluate the trade-offs among them. Finally, we discuss how facilitated forms of MCDA, where the model is created and analysed directly with a group of decision-makers in a decision conference, can tackle different aspects associated with government decision making and provide effective support in dealing with robustness of strategic decisions in designing complex policies with long-term consequences.

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