An appropriate supply chain design helps survival in competitive markets. Achieving maximum efficiency may also help decision makers have a better selection for the supply chain network. The purpose of this paper is to design an efficient supply chain model in terms of the distribution channels under uncertain conditions. The proposed study produces multi products using different materials by considering four layers of multiple suppliers, producers, storages and customers. There are two objectives of maximizing efficiency of distributers and minimizing total cost of supply chain management. The proposed model locates producers as well as suppliers and determines the amount of orders from different suppliers. In order to measure the relative efficiency, the study uses the method developed by Klimberg and Ratick (2008) [Klimberg, R. K., & Ratick, S. J. (2008). Modeling data envelopment analysis (DEA) efficient location/allocation decisions. Computers & Operations Research, 35(2), 457-474.]. In addition, to handle the uncertainty, the study uses the robust optimization technique developed by Molvey and Ruszczy?ski (1995) [Mulvey, J. M., & Ruszczy?ski, A. (1995). A new scenario decomposition method for large-scale stochastic optimization. Operations research, 43(3), 477-490.]. The preliminary results indicate that the proposed model is capable of providing efficient solutions under various uncertain conditions.

This paper presents a supply chain management by considering efficiency in the system. The proposed study considers two objective functions where the first one maximizes the efficiency of the supply chain and the second one minimizes the cost of facility layout as well as production of different products. In order to measure the relative efficiency, the study uses the method developed by Klimberg and Ratick (2008) [Klimberg, R. K., & Ratick, S. J. (2008). Modeling data envelopment analysis (DEA) efficient location/allocation decisions. Computers & Operations Research, 35(2), 457-474.]. The study has been formulated as a mixed integer programming and the implementation of the proposed model has been demonstrated using some numerical example. The preliminary results indicate that it was possible to increase the efficiency of supply chain without increase the supply chain expenses.