TY - JOUR ID - 2736 TI - The Use of Metaheuristics for a Stochastic Supply Chain Design Problem’s Resolution –A Comparison Study– JO - International Journal of Supply and Operations Management JA - IJSOM LA - en SN - 23831359 AU - Maliki, Fouad AU - Souier, Mehdi AU - Dahane, Mohammed AU - Sari, Zaki AD - Manufacturing Engineering Laboratory of Tlemcen, Tlemcen, Algeria AD - Laboratory of Industrial Engineering of Production and Maintenance, Metz, France Y1 - 2017 PY - 2017 VL - 4 IS - 3 SP - 193 EP - 201 KW - Distribution network KW - Suppliers selection KW - Metaheustics KW - Optimization DO - 10.22034/2017.3.01 N2 - In a competitive and maintainability context, each company finds to optimize her supply chain in order to maintain her customers by providing the best quality of products in the best delays and with the lost costs. In this sense, we are interested to a single commodity stochastic supply chain design problem. Our supply chain is composed of suppliers and retailers; the objective is to find the best location of distribution centres (DCs) and to serve retailers from suppliers trough DCs in a random supply lead time. We presented a non-linear optimization model integrated selection of suppliers, the location of DCs, and retailers allocation decisions with an oriented cost function to minimize. Note that the determination of exact solutions for this problem is a NP-hard problem. Accordingly, we propose an optimization approach using three different metaheuristics: genetic algorithm, simulated annealing and taboo search to solve this problem in order to find the best supply chain structure (location of DCs, allocation of suppliers to DCs and DCs to retailers). Computational results are presented and compared to evaluate the efficiency of the proposed approaches. UR - http://www.ijsom.com/article_2736.html L1 - http://www.ijsom.com/article_2736_9b46635d9fec65755119970fb6abcd53.pdf ER -