1 AIT Asian Institute of Technology

Meta-heuristic for a multi-objective multi-commodity distribution network with environmental considerations

AuthorRatnayake, Ratnayake Mudiyanselage Malika Nisal
NoteA thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Industrial and Manufacturing Engineering
PublisherAsian Institute of Technology
AbstractThe research presents a multi-objective model forsolving location-allocation problem (LAP) for a distribution network with environmental concerns. It involves the determination of the best strategy to distribute the product in a distribution network by selecting proper locations of suppliers, plants and distribution centers as well as the allocation of raw materials for suppliers to plants, allocation of products from plants to distribution centers to customers. Two objective functions are considered simultaneously. The first objective is to minimize the total costs and the second objective is to minimize the total amount of greenhouse gases generated by the activities. The model is validated using the test data that were derived from published benchmark test data set. The mathematical model was solved using CPLEX by converting one objective into a constraint with slack. The set of trade-off solutions is generated by solving the model repeatedly with varying slack values. The proposed mathematical model was then solved for single objective and multi-objectives using the Particle Swarm Optimization (PSO) and Differential Evolution (DE) techniques. An improved method of encoding and decoding was proposed to allocate products among the facilities. The model was first solved for single objectives using meta-heuristics in order to validate the proposed algorithm. Then the Pareto front of multi-objective objective optimization was obtained by optimizing both objective functions simultaneously. For this, multi-objective variants of PSO and DE was used. Several experiments were conducted with different iterations and movement/mutation strategies in order to achieve the best Pareto front.
Year2017
TypeThesis
SchoolSchool of Engineering and Technology (SET)
DepartmentDepartment of Industrial Systems Engineering (DISE)
Academic Program/FoSMicroelectronics (ME)
Chairperson(s)Huynh Trung Luong;Voratas Kachitvichyanukul
Examination Committee(s)Kanokporn Rienkhemaniyom;Mongkol Ekpanyapong
Scholarship Donor(s)AIT Fellowship
DegreeThesis (M. Eng.) -- Asian Institute of Technology, 2017


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