Weijun Xie (Industrial and Systems Engineering, Virginia Tech) is selected as the winner of the 2020 INFORMS Optimization Society Young Researchers Paper Prize
Weijun Xie is awarded the 2020 INFORMS Optimization Society Prize for Young Researchers for his paper, "On Distributionally Robust Chance Constrained Programs with Wasserstein Distance," Mathematical Programming (Series A), to appear. The paper studies the distributionally robust chance constrained program specifically with Wasserstein ambiguity set (DRCCP-W), i.e., the variable probability distribution is modeled using the Wasserstein distance from a given, empirical distribution. Compared with prior studies, which have used other types of ambiguity sets, the current paper settles the open question as to whether DRCCP with the highly desirable Wasserstein set can be optimized by means of a computable reformulation. Specifically, the paper shows: a conditional-value-at-risk formulation of DRCCP-W that allows tighter inner and outer approximations; a big-M mixed-integer formulation when the feasible region is bounded; and also a big-M-free formulation when the decision variables are binary. The paper also includes a careful numerical study supporting the effectiveness of the various formulations.
Sam Burer (chair), Hande Benson, Santanu Dey, Siqian Shen