Data-Driven Chance Constrained Programs over Wasserstein Balls

2018/09/01 by Zhi Chen, Daniel Kühn, Chen, Zhi +3 · 1 citation
Decision Sciences · Economics, Econometrics and Finance · #FOS: Mathematics #Health Systems, Economic Evaluations, Quality of Life #Optimization and Control (math.OC) #Risk and Portfolio Optimization

paper · pdf · doi:10.48550/arxiv.1809.00210

openalex publication_date 2018/09/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We provide an exact deterministic reformulation for data-driven chance constrained programs over Wasserstein balls. For individual chance constraints as well as joint chance constraints with right-hand side uncertainty, our reformulation amounts to a mixed-integer conic program. In the special case of a Wasserstein ball with the 1-norm or the ∞-norm, the cone is the nonnegative orthant, and the chance constrained program can be reformulated as a mixed-integer linear program. Our reformulation compares favourably to several state-of-the-art data-driven optimization schemes in our numerical experiments.

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