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Computing Optimality Certificates for Convex Mixed-Integer Nonlinear Problems

Author

Listed:
  • Katrin Halbig

    (Department of Data Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany)

  • Lukas Hümbs

    (Department of Data Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany)

  • Florian Rösel

    (Department of Data Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany)

  • Lars Schewe

    (School of Mathematics and Maxwell Institute for Mathematical Sciences, University of Edinburgh, Edinburgh EH9 3FD, United Kingdom)

  • Dieter Weninger

    (Department of Data Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91058 Erlangen, Germany)

Abstract

Every optimization problem has a corresponding verification problem that checks whether a given optimal solution is in fact optimal. In the literature, there are a lot of such ways to verify optimality for a given solution, for example, the branch-and-bound tree. To simplify this task, optimality certificates were introduced for convex mixed-integer nonlinear programs, and it was shown that the sizes of the certificates are bounded in terms of the number of integer variables. We introduce an algorithm to compute the certificates and conduct computational experiments. Through the experiments, we show that the optimality certificates can be surprisingly small.

Suggested Citation

  • Katrin Halbig & Lukas Hümbs & Florian Rösel & Lars Schewe & Dieter Weninger, 2024. "Computing Optimality Certificates for Convex Mixed-Integer Nonlinear Problems," INFORMS Journal on Computing, INFORMS, vol. 36(6), pages 1579-1610, December.
    • Handle: RePEc:inm:orijoc:v:36:y:2024:i:6:p:1579-1610
    DOI: 10.1287/ijoc.2022.0099
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    References listed on IDEAS

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