logistica transporte de carga
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logistica en transporte de carga en el pais mediante algoritmo heuristico y metaheuristicos, por problemas multi objetivos, transporte de cargaTRANSCRIPT
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DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithms.DSS para la planeacin de transporte de mercanca a nivel urbano basado en algoritmos heursticos y metaheursticos
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsPresentation Outline
Brief introductionProblem descriptionMathematical model formulationSolution approaches given in literatureHeuristic and Metaheuristic Algorithms implemented in the DSSSoftware Development Methodology AppliedDevelopment and Implementation
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsBrief Introduction
Optimal planning of the logistic network has been a broad area of study and most interesting topic among researches in the fieldThis study was based on the preliminary results obtained from the ongoing project entitled Desarrollo de Sistemas Inteligentes de Gestin de Transporte para soporte a la toma de decisiones operativas urbanas, which implies the construction of software that directs the optimal routing and allocation of trucks in the city in their daily planning program.A programming methodology is used, which has been proven to facilitate the integration of many decision procedures or algorithms in the decision making tool, thus making it more flexible to implement in real life situationsAlgorithms selected for each functionality of the program are presentedThe integration of these algorithms in the DSS tool are proven to generate good solutions
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsProblem Description
The logistic operation of a company at a daily basis implies a series of activities: Orders managementFleet administration allocation of vehiclesDistribution managementCapacity planningRoute designControl and follow-up
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsShortest Path ProblemTransportation ProblemAssignment ProblemTransshipment ProblemVehicle Routing ProblemOptimal Network Design ProblemSpanning Tree ProblemNetwork Flow ProblemMultiobjective Transportation Network DesignFig 1. Multiobjective Transportation network and its basic instances (source: Current & Marsh, 1993)
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsProblem Description Designing optimal routesOne of the main subjects of attention in the scientific community has been with respect to the vehicle routing problem (VRP), first defined by Dantzig and Ramser in 1959 The vehicle-routing problem (VRP) consists on assigning sequences to the vehicles that must visit each one of the customers in the service area in order to minimize time of the total route or transportation costs.The VRP is described as a directed graph G(A,V), where V= {0,1,n} represents a set of nodes and A is the set of arcs that connect each one of the nodes. In real life applications, this problem has been approached under multiple variants:VRPTWHFVRPMDVRPCVRPVRPPD
Fig 2. VRP as the TSP problem
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsProblem Description allocation of vehicles and capacity planningThe daily operation also implies capacity planning and allocation of vehicles, even more if the planning involves multiple depots were merchandize is dispatchedA mathematical allocation problem is usually formulated, where capacities are also considered. This classical allocation problem is considered NP-complete.When integrating the classical allocation problem with VRP, its complexity increases. Most authors are implementing the location-routing problem (LRP), due to the fact that the facilities location or allocation of clients in several clusters can be dynamically changed and thus the routes considered previously.The location-routing problem (LRP) implies both the allocation and routing of vehicles, allowing the program to determine the capacity and/or size of the facilities and vehicles. Given a set of potential depots with opening costs, a fleet of identical vehicles and a set of customers with known demands, the classical LRP consists in opening a subset of depots, assigning customers to them and determining vehicle routes, to minimize a total cost including the cost of open depots, the fixed costs of vehicles used, and the total cost of the routes [Prodhon and Prins, 2014].
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithms
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithms
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsSolution approaches given in literature VRP and its variants
Exact algorithmsHeuristic algorithms
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsSolution approaches given in literature VRP and its variants
MetaheuristicHybrid
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsSolution approaches given in literature LRP
Breakthrough: Hybrid Algorithms!
Combining 2 metaheuristicsFor example: GRASP with Path Relinking
Combining a metaheuristic with an exact methodSpecial attention given to: Multiobjective problems
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsSolution approaches given in literature LRP
Table 1. Source: PRODHON & PRINS, A survey on recent research on location-routing problems, EJOR, 238 (2014), 1-17.
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsHeuristic and Metaheuristic Algorithms implemented in the DSS
Ant Colony Optimization (ACO)Simulates Ants behavior when looking for foot sourcesLikewise the algorithm builds routes to visit costumers
EPSO Evolutionary Particle Swarm OptimizationRoute construction and optimization - VRPTWAllocation of customers and vehiclesReplicationMutationReproductionFitnessSelection
LRP
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsHeuristic and Metaheuristic Algorithms implemented
Proposed GA pseudo-code
Create an initial population of individualsWhile termination condition not satisfied doRepeatIf crossover condition satisfied thenSelect parentsPerform crossoverEnd ifIf mutation condition satisfied thenPerform mutationEnd ifEvaluate fitness of offspringUntil sufficient offspring createdSelect new populationEnd whileGenerating new feasible solutions for multiple objectives Cost and Time objectivesGenetic AlgorithmGenetic Algorithm GA is an evolutionary approach for a large type of combinatorial optimization problems that uses the concepts of mutation and selection from Darwinian theory of evolution.
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsSoftware Development Methodology AppliedEriccsonObjectoryUML SysMLRUP -Open UPOthersSix SigmaITILCMMIOthers
Agile ManifestoXPSCRUMICONIXLeanOthers
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsDevelopment and Implementation
Domain Model
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsDevelopment and Implementation
Use Case ModelRobustness Model
Sequence Diagram
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsDevelopment and Implementation
Data Model
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsDevelopment and ImplementationArchitecture
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsRESEARCH GROUP:
Carlos Javier UribeRuben SnchezNilson HerazoLauren CastroFairuz OspinoHenry MauryHeyder PaezDiana G. Ramrez AcknowledgementsThis research was possible under the financial support of the Atlantic Department Government and the Colombian General Royalties System, through the project LOGPORT.
DSS for the planning of urban freight transportation based on heuristic and metaheuristic algorithmsTHANK YOU!Gracias!Diana G. Ramrez-Ros, MSc. Industrial EngineerPhD student in Transportation Engineering starting Fall 2015Research Assistant LOGPORT-CUCAdjunct Assistant [email protected]@gmail.comSkype: diana.g.ramirezHeyder Paez Logreira Electronic EngineerMSc. Student in Systems Engineering and CSResearch Assistant LOGPORT-CUCAssistant [email protected]@gmail.comSkype: heyderpaez
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