A novel two-stage stochastic model for supply chain network design under uncertainty

This paper addresses the problem of designing a supply chain network consisting of suppliers, manufacturers, warehouses, and customers in which all manufacturers belong to a single owner. All players in this chain are performing under uncertainty. The single product of this supply chain needs one strategic and one non-strategic part for its nal assembly. To hedge against uncertainty in supply and demand, the manufacturers tend to take part in a set of suppliers through a portfolio of contracts, and unmet demand will be satis ed by purchasing from spot market with stochastic prices. In addition, demands, supply capacities, and warehouse capacities are stochastic as well, and the problem has been modeled as a two-stage stochastic program with recourse. Then, a hybrid solution strategy based on sample average approximation and accelerated Benders decomposition is proposed to tackle the problem. The proposed strategy is able to obtain good quality solutions for a large number of scenarios and within an acceptable time interval. Computational results show the e ectiveness of the stochastic model as compared to its deterministic counterpart.