NDLI: Models and algorithms for two-echelon capacitated facility location problem with facility size selection

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Models and algorithms for two-echelon capacitated facility location problem with facility size selection

Content Provider	Semantic Scholar
Author	Wu, Tingying
Copyright Year	2015
Abstract	Facility location is one of the most important strategic decisions for firms in globalization. Previous works on facility location in the literature mainly focus on determining the locations of facilities and the flows of products from facilities to customers with the goal of minimizing the sum of facility opening costs, production and logistic costs. However, it’s very important to determine at the same time the appropriate sizes for these facilities because they greatly affects these costs on the long term. Determining facility location and size is always an open problem.In this thesis, we study three new two-echelon capacitated facility location problems (TECFLP) with facility size selection. The two first parts of the wok focus on two-echelon facility location problems with plant and depot size selection, respectively. The third part concentrates on TECFLP considering simultaneously plant and depot size selection. For these problems, three corresponding mixed integer programming models are formulated and then Lagrangean relaxation approaches according to the problems’ characteristics are developed. To further improve the best solutions obtained by the Lagrangean Relaxation approaches, a tabu search, a hybrid variable neighborhood tabu search and a hybrid simulated annealing tabu search are adapted for the three problems respectively. The developed algorithms are tested and evaluated through 810 randomly generated instances. Computational results show ours algorithms can provide high quality solutions within a reasonable computation time.
File Format	PDF HTM / HTML
Alternate Webpage(s)	https://hal.archives-ouvertes.fr/tel-01758586/document
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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