Stochastic Programs with First-Order Dominance Constraints Induced by Mixed-Integer Linear Recourse

We propose a new class of stochastic integer programs whose special features are dominance constraints induced by mixed-integer linear recourse. For these models, we establish closedness of the constraint set mapping with the underlying probability measure as parameter. In the case of finite probability spaces, the models are shown to be equivalent to large-scale, block-structured, mixedinteger linear programs. We propose a decomposition algorithm for the latter and discuss preliminary computational results.