Resolution of a stochastic supply chain design problem by metaheuristic

Author

Maliki, Fouad ; Sari, Z. ; Souier, M.

Author_Institution

Lab. de productique de Tlemcen (MELT), Univ. Abou Bekr-Belkaid, Tlemcen, Algeria

fYear

2013

fDate

6-8 May 2013

Firstpage

366

Lastpage

371

Abstract

This work addresses a study of a single commodity stochastic distribution network. The distribution network under consideration consists of a set of suppliers serving in a random delivery time a set of retailers through a set of distribution centers (DCs); suppliers are linked to retailers by a single way. So, strategic decisions of suppliers´ selection, DCs location and retailers assignment are integrated in one nonlinear optimization model. Our objective is to find the number of DCs to open and their best location, the best allocation of suppliers to DCs and DCs to retailers. A simulation based optimization approach using Multi-Objective Genetic Algorithm (MOGA) is used to solve this problem. So, numerical results are presented and analyzed to show the effectiveness of the proposed approach.

Keywords

genetic algorithms; nonlinear programming; resource allocation; retailing; supply chain management; DCs location; MOGA; distribution centers; metaheuristic; multiobjective genetic algorithm; nonlinear optimization model; retailers; simulation based optimization approach; stochastic distribution network; stochastic supply chain design problem; Biological cells; Genetic algorithms; Numerical models; Optimization; Resource management; Sociology; Supply chains; MOGA; Optimization; distribution network; simulation;

fLanguage

English

Publisher

ieee

Conference_Titel

Control, Decision and Information Technologies (CoDIT), 2013 International Conference on

Conference_Location

Hammamet

Print_ISBN

978-1-4673-5547-6

Type

conf

DOI

10.1109/CoDIT.2013.6689572

Filename

6689572