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Distributionally Robust Optimization with Polynomial Robust Constraints

Author

Listed:
  • Jiawang Nie

    (University of California San Diego)

  • Suhan Zhong

    (Texas A&M University)

Abstract

This paper studies distributionally robust optimization (DRO) with polynomial robust constraints. We give a Moment-SOS relaxation approach to solve the DRO. This reduces to solving linear conic optimization with semidefinite constraints. When the DRO problem is SOS-convex, we show that it is equivalent to the linear conic relaxation and it can be solved by the Moment-SOS algorithm. For nonconvex cases, we also give concrete conditions such that the DRO can be solved globally. Numerical experiments are given to show the efficiency of the method.

Suggested Citation

  • Jiawang Nie & Suhan Zhong, 2025. "Distributionally Robust Optimization with Polynomial Robust Constraints," Journal of Global Optimization, Springer, vol. 92(3), pages 509-534, July.
    • Handle: RePEc:spr:jglopt:v:92:y:2025:i:3:d:10.1007_s10898-025-01504-6
    DOI: 10.1007/s10898-025-01504-6
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