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Making Robust Decisions in Discrete Optimization Problems as a Game against Nature

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Abstract

In this paper a discrete optimization problem under uncertainty is discussed. Solving such a problem can be seen as a game against nature. In order to choose a solution, the minmax and minmax regret criteria can be applied. In this paper an extension of the known minmax (regret) approach is proposed. It is shown how different types of uncertainty can be simultaneously taken into account. Some exact and approximation algorithms for choosing a best solution are constructed.

Suggested Citation

  • Adam Kasperski, 2008. "Making Robust Decisions in Discrete Optimization Problems as a Game against Nature," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 2(3), pages 237-250, December.
  • Handle: RePEc:fau:aucocz:au2008_237
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    File URL: http://auco.fsv.cuni.cz/storage/48_2008_03_237.pdf
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    References listed on IDEAS

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    1. Montemanni, R. & Gambardella, L. M., 2005. "A branch and bound algorithm for the robust spanning tree problem with interval data," European Journal of Operational Research, Elsevier, vol. 161(3), pages 771-779, March.
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    Keywords

    Discrete optimization; minmax; minmax regret; game against nature;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C79 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Other

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