Developing a location-inventory model under fuzzy environment

Nowadays, location of distribution centers integrated with inventory or transportation decision play an important role in optimizing supply chain management. Location-inventory models analyze the location and inventory policies in distribution network, simultaneously. Developing location-inventory models under fuzzy environment can enrich the model, and this is our approach in this article. We consider the demand as a fuzzy variable and formulate the problem using credibility theory in order to locate distribution centers (DCs) as well as determining inventory levels in DCs. The derived model belongs to nonlinear mixed integer programming problems, and we presented a genetic algorithm to solve it. Numerical results show that the performance of the proposed algorithm is reasonable.