Distributionally Robust Stochastic Programming

Abstract

Abstract. In this paper we study distributionally robust stochastic programming in a setting 7 where there is a specified reference probability measure and the uncertainty set of probability mea8 sures consists of measures in some sense close to the reference measure. We discuss law invariance of 9 the associated worst case functional and consider two basic constructions of such uncertainty sets. 10 Finally we illustrate some implications of the property of law invariance. 11

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Cite this paper

@inproceedings{Shapiro2016DistributionallyRS, title={Distributionally Robust Stochastic Programming}, author={Alexander Shapiro}, year={2016} }