There are many valuable studies reported in the current literature of supply chain, but considerable gaps include integration and insertion of basic concepts, such as queuing theory, facility location, inventory management, or even uncertainty and stochastic environment still prevail. In this article a supply chain network design model has been developed by considering Multi-echelon, multi-objective forward/reverse logistics under uncertainty. The proposed model encompasses inventory and facility location planning, simultaneously to make the model closer to the real world problems. For the proposed model we use scenario-based stochastic approach and a robust optimization approach is proposed to deal with this important issue. An efficient genetic algorithm is applied to determine the Pareto optimal solutions.
