An Integrated Model and Algorithm for Facility Location under Uncertainty

In this paper, we present an integrated approach for simultaneous optimization of the facility location and capacity level of selected facilities under uncertainty. Existing approaches for facility location are usually restricted to only single determining capacity for alternative facilities, and we extend it to several alternative level of capacity for each potential facility so as to avoid the output surplus or scarcity in the future. For this issue, we propose a deterministic formulation and a two-stage stochastic programming model under uncertain environment. In addition, we design two Benders decomposition algorithms for our problems and implement them in matlabl.O. We report on a set of experiments, and conclude that the computational performance of the proposed algorithms is quite satisfactory.