A Modified Benders Decomposition Algorithm for Supply Chain Network Design under Risk Consideration

In today’s competitive business environment, the design and management of supply chain network is one of the most important challenges that managers encounter. The supply chain network should be designed for satisfying of customer demands as well as minizing the total system costs. This paper presents a multi-period multi-stage supply chain network design problem under demand uncertainty. The problem is formulated as a two-stage stochastic program. In the first-stage, strategic location decisions are made, while the second-stage contains the tactical decisions. In our developed model, conditional value-at-risk (CVaR) as an effective risk measure is used to produce first-stage decisions in which the loss cost in the second-stage is minimized. In addition, a modified Benders decomposition algorithm is developed to solve the model exactly. The computational results on a set of randomly generated problem instances demonstrate the effectiveness of the proposed algorithm in terms of the solution quality.