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Minkowski Centers via Robust Optimization: Computation and Applications

Author

Listed:
  • Dick den Hertog

    (Amsterdam Business School, University of Amsterdam, 1001 NL Amsterdam, Netherlands)

  • Jean Pauphilet

    (Management Science and Operations, London Business School, London NW1 4SA, United Kingdom)

  • Mohamed Yahya Soali

    (Industrial Engineering and Operations Research, Columbia University, New York, New York 10027)

Abstract

Centers of convex sets are geometric objects that have received extensive attention in the mathematical and optimization literature, both from a theoretical and practical standpoint. For instance, they serve as initialization points for many algorithms such as interior-point, hit-and-run, or cutting-planes methods. First, we observe that computing a Minkowski center of a convex set can be formulated as the solution of a robust optimization problem. As such, we can derive tractable formulations for computing Minkowski centers of polyhedra and convex hulls. Computationally, we illustrate that using Minkowski centers, instead of analytic or Chebyshev centers, improves the convergence of hit-and-run and cutting-plane algorithms. We also provide efficient numerical strategies for computing centers of the projection of polyhedra and of the intersection of two ellipsoids. Supplemental Material: The online appendix is available at https://doi.org/10.1287/opre.2023.2448 .

Suggested Citation

  • Dick den Hertog & Jean Pauphilet & Mohamed Yahya Soali, 2024. "Minkowski Centers via Robust Optimization: Computation and Applications," Operations Research, INFORMS, vol. 72(5), pages 2135-2152, September.
    • Handle: RePEc:inm:oropre:v:72:y:2024:i:5:p:2135-2152
    DOI: 10.1287/opre.2023.2448
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