END332E Operations Research II

Y. İlker TOPCU, Ph.D.

www.ilkertopcu.net www.ilkertopcu.org www.ilkertopcu.info

www.facebook.com/yitopcu

twitter.com/yitopcu

Özgür KABAK, Ph.D.web.itu.edu.tr/kabak/

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Credits: 3+0

ECTS Credits: 7

Type: Compulsory

Language: English

Web site: web.itu.edu.tr/topcuil/ya/END332E

ninova.itu.edu.tr

Course Information

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Integer Programming

Branch and Bound / Cutting Planes Algorithms

Combinatorial Optimization

Multi objective decision making (Goal Programming)

Multi attribute decision making (SAW, WP, TOPSIS)

Non-Linear Programming

Interior point algorithms

Dynamic Programming

Course description

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1. To use different mathematical modeling techniques utilizing Operations Research (OR) methodology

2. To learn various methods that are used for quantitative decision making

3. To find optimal solutions to problems

Course objectives

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Students who pass the course will gain1. ability to formulate and solve Integer Programming

problems2. insight in Combinatorial Optimization3. insight in Multi Objective (Goal Programming) and

Multi Attribute Decision Making4. ability to formulate and solve Non-Linear

Programming problems5. ability to formulate and solve Dynamic

Programming problems

Course learning outcomes

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Relationship between the course and Industrial Engineering curriculum

1: Little, 2. Partial, 3. Full

Program Outcomes 1 2 3

a Apply mathematics, science, and engineering principles X

b Ability to design and conduct experiments and interpret data

c Ability to design a system, component, or process to meet desired needs X

d Ability to function on multidisciplinary teams X

e Abiliy to identify, formulate, and solve engineering problems X

f Understanding of professional and ethical responsibility X

g Ability to communicate effectively

hThe broad education necessary to understand the impact of engineering solutions in a global context

i Recognition of the need for and an ability to engage in a life-time education

j Knowledge of contemporary issues

kAbility to use the techniques, skills, and modern engineering tools necessary for engineering practice

X

l Ability to apply his/her knowledge in business X

m Knowledge and skills of management X

nUnderstanding of the environment and responsibility for changes in technological, economical and social issues

o To have a high degree of self-confidence and initiative

Level of Contribution

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Text book Winston W.L. (2004) “Operations Research: Applications and

Algorithms”, Brooks/Cole – Thomson Learning

Web site of the course Up-to-date lecture notes and supplements Solutions to exams and homework Previous exam questions

Books “Operations Research”, "Practical Management Science",

"Introduction to Management Science“, "Quantitative Analysis for Management”, "Optimization in Operations Research", "Introduction to Mathematical Programming“

Web sites of other courses

References

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Final exam (40%), 2 Midterm exams (40%),

3 Assignments (20%)

All exams will be “open book”

If your final exam grade is less than 30 or if your average grade is less than 40, you will receive a letter grade FF

If you do not complete the following requirements, you will receive a letter grade VF: One of your midterm exam grades must be

more than 30 One of your HW grades must be more than 50

Assessment Criteria

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Exams

Midterm exam 1

Topics covered in the first six weeks

March 18, 6:00 pm

Midterm exam 2

Topics covered after week seven

May 6, 6:00 pm

Final exam

All topics

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Assignments

HW1

Integer Programming

February 25 – March 11

HW2

Non-linear programming, Interior Point algorithms

April 1 – April 15

HW3

Dynamic Programming

April 29 – May 13

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Do not!

Studying together to understand the material is fine, but the work you hand in is to be your own.

No cheating will be tolerated: A letter grade of F will be given!

You can constitute a group of maximum three students to submit assignments. You may submit a unique report for your group (of course plagiarism among assignment groups is strictly forbidden).

Cheating and Plagiarism

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ScheduleFeb. 2-4 I nteger Programming, Formulating I P Problems

Feb. 9 Formulating I P Problems (cont.) no class on Feb. 11

Feb. 16-18 Solving I P Problems

Feb. 23-25 Solving I P Problems (cont.)

Mar. 2-4 Multiobjective: Goal Programming

Mar. 9-11 Multiattribute: SAW, WP, TOPSI S

Mar. 16 (Mon.) PROBLEM SOLVI NG

Mar. 18 (Wed.) MI DTERM I (18:00)

Mar. 23-25 I ntroduction to Non-Linear Programming

Mar. 30 – Apr. 1 I nt. to NLP (cont.), I nterior Point Methods

Apr. 6-8 Deterministic Dynamic Programming

Apr. 13-15 Deterministic Dynamic Programming (cont.)

Apr. 20–22 Probabilistic Dynamic Programming

Apr. 27-29 Probabilistic Dynamic Programming (cont.)

May 4 (Mon.) PROBLEM SOLVI NG

May 6 (Wed.) MI DTERM I I (18:00)

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Asst. Prof. Dr. Özgür Kabak

Office address

Management Faculty A311, Maçka, Istanbul 

Phone

(212) 293 1300  /2039 office   /2073 secretary 

Web site

web.itu.edu.tr/kabak/

E-mail address

kabak@itu.edu.tr

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Asst. Prof. at Industrial Engineering department of ITU (2011)

Post-doc studies at Belgium Nuclear Research Centre (SCK.CEN) (2009-2010)

A fuzzy multi attribute decision making approach for nuclear safeguards information management

Ph.D. in ITU Industrial Engineering programme (2008)

Modeling supply chain network using possibilistic linear programming and an application

Research interests

Operations Research (Mathematical programming)

Supply chain management

Fuzzy decision making

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Prof. Dr. Y. İlker Topcu

Office address

Management Faculty C301, Maçka, Istanbul 

Phone

(212) 293 1300  /2069 office - (532) 355 5045 mobile 

Web site

www.ilkertopcu.net, www.ilkertopcu.org, www.ilkertopcu.info,

www.facebook.com/yitopcu, twitter.com/yitopcu

E-mail address

ilker.topcu@itu.edu.tr

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Professor at Industrial Engineering department of ITU (2011)

Associate Professorship in Operations Research (2005)

Ph.D. in ITU Engineering Management programme (2000)

Integrated decision aid model for multi-attribute problem solving

Ph.D. research at Centre for Decision Research of Leeds University Business School (1998-1999)

Research interests

Decision Analysis, Multi Criteria Decision Making, Group Decision Making

Operations Research / Management Science

Logistics Management, Ethics in OR, Business Ethics, Transp’n, Energy, Bidding and Tender Systems, Scheduling