@article { author = {Salehi, Hossein and Tavakkoli-Moghaddam, Reza and Taleizadeh, Ata Allah and Hafezalkotob, Ashkan}, title = {Solving a location-allocation problem by a fuzzy self-adaptive NSGA-II}, journal = {Journal of Industrial and Systems Engineering}, volume = {12}, number = {4}, pages = {18-26}, year = {2019}, publisher = {Iranian Institute of Industrial Engineering}, issn = {1735-8272}, eissn = {2717-3380}, doi = {}, abstract = {This paper proposes a modified non-dominated sorting genetic algorithm (NSGA-II) for a bi-objective location-allocation model. TheĀ purpose is to define the best places and capacity of the distribution centers as well as to allocate consumers, in such a way that uncertain consumers demands are satisfied. The objectives of the mixed-integer non-linear programming (MINLP) model are to (1) minimize the total cost of the network and (2) maximize the utilization of distribution centers. To solve the problem, a fuzzy modified NSGA-II with local search is proposed. To illustrate the results, computational experiments are generated and solved. The experimental results demonstrate that the performance metrics of the fuzzy modified NSGA-II is better than the original NSGA-II.}, keywords = {location-allocation,fuzzy rule base,multi-objective evolutionary algorithm}, url = {https://www.jise.ir/article_95549.html}, eprint = {https://www.jise.ir/article_95549_1446f854ec996cc37b4f54a3497bf8ff.pdf} }