Minkowski Centers via Robust Optimization: Computation and Applications

Centers of convex sets are geometrical 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 polyhedra and convex hulls. Computationally, we illustrate that using Minkowski centers, instead of the analytic or Chebyshev center, 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.

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