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Confidence sets for discrete stochastic optimization

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Abstract

Consider the problem of finding the points of maximum of an expectation functional over a finite setS. Based on statistical estimates at each point ofS, confidence sets for theargmax-set are constructed which guarantee a prespecified probability of correct selection. We review known selection methods and propose a new two-stage procedure that works well for largeS and few global maxima. The performance is compared in a simulation study.

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Authors and Affiliations

  1. Department of Mathematics, University of Vienna, Vienna, Austria

    A. Futschik & G. Pflug

Authors
  1. A. Futschik
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  2. G. Pflug
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Futschik, A., Pflug, G. Confidence sets for discrete stochastic optimization. Ann Oper Res 56, 95–108 (1995). https://doi.org/10.1007/BF02031702

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  • DOI: https://doi.org/10.1007/BF02031702

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