Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8051708 | Applied Mathematical Modelling | 2018 | 24 Pages |
Abstract
We consider distributionally robust two-stage stochastic convex programming problems, in which the recourse problem is linear. Other than analyzing these new models case by case for different ambiguity sets, we adopt a unified form of ambiguity sets proposed by Wiesemann, Kuhn and Sim, and extend their analysis from a single stochastic constraint to the two-stage stochastic programming setting. It is shown that under a standard set of regularity conditions, this class of problems can be converted to a conic optimization problem. Numerical results are presented to show the efficiency of the distributionally robust approach.
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Authors
Bin Li, Xun Qian, Jie Sun, Kok Lay Teo, Changjun Yu,