Hybrid approach for solving the multiobjective facility location problem /
منهجية مختلطة لحل مشكلة تحديد مواقع تقديم التسهيلات ذات الاهداف المتعددة
Ahmed Abdelhameed Abdelaziz Eldesouky Zakzouk ; Supervised Mohamed Sayed Ali Osman , Ramadan Abdelhameed Zean Eddin , Hamdeen Abdelwahid Khalifa
- Cairo : Ahmed Abdelhameed Abdelaziz Eldesouky Zakzouk , 2019
- 123 Leaves : charts , facsimiles ; 30cm
Thesis (Ph.D.) - Cairo University - Faculty of Graduate Studies for Statistical Research - Department of Operations Research
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
Big Bang Big Crunch Facility Location Problem Multiobjective Optimization