Risk Aversion via Excess Probabilities in Stochastic Programs with Mixed-Integer Recourse

Abstract

We consider linear two-stage stochastic programs with mixed-integer recourse. Instead of basing the selection of an optimal first-stage solution on expected costs alone, we include into the objective a risk term reflecting the probability that a preselected cost threshold is exceeded. After we have put the resulting mean-risk model into perspective with stochastic dominance, we study further structural properties of the model and derive some basic stability results. In the algorithmic part of the paper, we propose a scenario decomposition method and report initial computational experience.

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