A modeling framework for stochastic multi-period capacitated multiple allocation hub location

We propose a two-stage stochastic programming modeling framework for multi-period multiple allocation hub location under uncertainty. A discretized planning horizon is considered and stochasticity is assumed for the flows to be routed through the network. When uncertainty can be described by a discrete random vector with a finite support it is possible to derive the extensive form of the deterministic equivalent. However, this results in a large-scale mixed-integer linear programming model that nonetheless can be enhanced using several families of valid inequalities. Computational tests performed using benchmark data are reported and show that the new sets of valid inequalities are able to provide a good polyhedral description of the feasibility set, which is of relevance