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Solving Robust Two-Stage Combinatorial Optimization Problems Under Convex Uncertainty

In: Operations Research Proceedings 2019

Author

Listed:
  • Marc Goerigk

    (University of Siegen)

  • Adam Kasperski

    (Wrocław University of Science and Technology)

  • Paweł Zieliński

    (Wrocław University of Science and Technology)

Abstract

In this paper a class of robust two-stage combinatorial optimization problems with uncertain costs is discussed. It is assumed that the uncertainty is modeled by using a convex uncertainty set, for example of polyhedral or ellipsoidal shape. Several methods to compute exact and approximate solutions are introduced. Experimental results for robust two-stage version of the weighted set cover problem are presented.

Suggested Citation

  • Marc Goerigk & Adam Kasperski & Paweł Zieliński, 2020. "Solving Robust Two-Stage Combinatorial Optimization Problems Under Convex Uncertainty," Operations Research Proceedings, in: Janis S. Neufeld & Udo Buscher & Rainer Lasch & Dominik Möst & Jörn Schönberger (ed.), Operations Research Proceedings 2019, pages 423-429, Springer.
    • Handle: RePEc:spr:oprchp:978-3-030-48439-2_51
    DOI: 10.1007/978-3-030-48439-2_51
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    Cited by:

    1. Marc Goerigk & Adam Kasperski & Paweł Zieliński, 2022. "Robust two-stage combinatorial optimization problems under convex second-stage cost uncertainty," Journal of Combinatorial Optimization, Springer, vol. 43(3), pages 497-527, April.

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