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Using Metrics in Stability of Stochastic Programming Problems
[Užití metrik ve stabilitě úloh stochastického programování]

Author

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  • Michal Houda

Abstract

Optimization techniques enter often as a mathematical tool into many economic applications. In these models, uncertainty is modelled via probability distribution that is approximated or estimated in real cases. Then we ask for a stability of solutions with respect to changes in the probability distribution. The work illustrates one of possible approaches (using probability metrics), underlying numerical challenges and a backward glance to economical interpretation.

Suggested Citation

  • Michal Houda, 2005. "Using Metrics in Stability of Stochastic Programming Problems [Užití metrik ve stabilitě úloh stochastického programování]," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2005(1), pages 128-134.
    • Handle: RePEc:prg:jnlaop:v:2005:y:2005:i:1:id:145:p:128-134
    DOI: 10.18267/j.aop.145
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    1. repec:czx:journl:v:9:y:2002:i:17:id:116 is not listed on IDEAS
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    More about this item

    Keywords

    stochastic programming; quantitative stability; Wasserstein metrics; Kolmogorov metrics; simulation study;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

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