الفهرس 
Title : Hybrid approach for solving the multiobjective facility location problem
SummaryOnly 14 pages are availabe for public view
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Abstract
This thesis presents a hybrid nature inspired optimization approach to solve the multi-objective facility location problem. It gives a good design to the models with network type specially using powerful meta-heuristic techniques, like big bang big crunch, pigeon inspired optimization and evolutionary algorithm which is a new trend in dealing with this type of the facility location problem.The proposed hybrid approach consists of one of the following approaches: either using the big bang big crunch technique with the evolutionary algorithm or using the pigeon inspired optimization with the evolutionary algorithm.The comparison between results determined the best values, time and the quickest convergence to the optimal state. The facility location problem aims to locate a new facility or more to a finite set of demands minimizing the cost according to some set of constraints. A lot of researchers took this type of problems as a challenge for a long time. A real problem and other problems from references are solved using the proposed approach, an implementation study and a parameter analysis are presented. The techniques BB-BC, PIO and EA give good performance, but PIO technique is more efficient with the EA technique, also the best values of the parameters of BB-BC and PIO techniques are determined which lead to best convergence to the optimal solution