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An asymptotic test of optimality conditions in multiresponse simulation optimization

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  • Angun, M.E.

    (Tilburg University, School of Economics and Management)

  • Kleijnen, Jack P.C.

    (Tilburg University, School of Economics and Management)

Abstract

This paper derives a novel, asymptotic statistical test of the Karush--Kuhn--Tucker first-order necessary optimality conditions in random simulation models with multiple responses. This test combines a simple form of the delta method and a generalized version of Wald's statistic. The test is applied to both a toy problem and an ( s , S ) inventory-optimization problem with a service-level constraint; its numerical results are encouraging.
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Suggested Citation

  • Angun, M.E. & Kleijnen, Jack P.C., 2012. "An asymptotic test of optimality conditions in multiresponse simulation optimization," Other publications TiSEM a69dfa59-b0e1-45bd-8cd6-a, Tilburg University, School of Economics and Management.
  • Handle: RePEc:tiu:tiutis:a69dfa59-b0e1-45bd-8cd6-a9529d4d8d96
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    1. Bettonvil, Bert & del Castillo, Enrique & Kleijnen, Jack P.C., 2009. "Statistical testing of optimality conditions in multiresponse simulation-based optimization," European Journal of Operational Research, Elsevier, vol. 199(2), pages 448-458, December.
    2. Sridhar Bashyam & Michael C. Fu, 1998. "Optimization of (s, S) Inventory Systems with Random Lead Times and a Service Level Constraint," Management Science, INFORMS, vol. 44(12-Part-2), pages 243-256, December.
    3. Safizadeh, M. Hossein, 2002. "Minimizing the bias and variance of the gradient estimate in RSM simulation studies," European Journal of Operational Research, Elsevier, vol. 136(1), pages 121-135, January.
    4. Kodde, David A & Palm, Franz C, 1986. "Wald Criteria for Jointly Testing Equality and Inequality Restriction s," Econometrica, Econometric Society, vol. 54(5), pages 1243-1248, September.
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