A sample average approximation approach for supply chain network design with facility disruptions

In this paper, we propose a sample average approximation (SAA) algorithm to solve the supply chain network design problem involving facility disruptions. This problem is formulated as a two-stage stochastic programming model as well as an explicit scenario-based model. We solve the models using SAA with a scenario decomposition algorithm to solve each sample problem. Three alternative subroutines for the scenario decomposition algorithm are proposed in order to accelerate the algorithm. The performances of these alternatives are compared in computational experiments. The results show that high-quality solutions with performance guaranty can be obtained through this proposed approach.