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Two-Stage Multiple Comparisons with the Best for Computer Simulation

Author

Listed:
  • Frank J. Matejcik

    (South Dakota School of Mines and Technology, Rapid City, South Dakota)

  • Barry L. Nelson

    (Northwestern University, Evanston, Illinois)

Abstract

We consider the problem of comparing a small number of stochastic systems via computer simulation when the basis for comparison is the expected value of some system performance measure. To solve this problem we develop two-stage sampling procedures that provide confidence intervals for the difference between the expected performance of each system and the best of the others. These confidence intervals are valid under mild conditions, and the procedures allow the experimenter to specify the desired precision in advance. Special cases of our results include standard indifference-zone selection procedures. The paper includes guidelines for experiment design and an illustrative example.

Suggested Citation

  • Frank J. Matejcik & Barry L. Nelson, 1995. "Two-Stage Multiple Comparisons with the Best for Computer Simulation," Operations Research, INFORMS, vol. 43(4), pages 633-640, August.
  • Handle: RePEc:inm:oropre:v:43:y:1995:i:4:p:633-640
    DOI: 10.1287/opre.43.4.633
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    Citations

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    Cited by:

    1. Barry L. Nelson & David Goldsman, 2001. "Comparisons with a Standard in Simulation Experiments," Management Science, INFORMS, vol. 47(3), pages 449-463, March.
    2. Sigurdur Ólafsson, 2004. "Two-Stage Nested Partitions Method for Stochastic Optimization," Methodology and Computing in Applied Probability, Springer, vol. 6(1), pages 5-27, March.
    3. Stephen E. Chick & Koichiro Inoue, 2001. "New Two-Stage and Sequential Procedures for Selecting the Best Simulated System," Operations Research, INFORMS, vol. 49(5), pages 732-743, October.
    4. Wang, Honggang, 2012. "Retrospective optimization of mixed-integer stochastic systems using dynamic simplex linear interpolation," European Journal of Operational Research, Elsevier, vol. 217(1), pages 141-148.
    5. John Butler & Douglas J. Morrice & Peter W. Mullarkey, 2001. "A Multiple Attribute Utility Theory Approach to Ranking and Selection," Management Science, INFORMS, vol. 47(6), pages 800-816, June.
    6. Nakayama, Marvin K., 2007. "Fixed-width multiple-comparison procedures using common random numbers for steady-state simulations," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1330-1349, November.
    7. Sidney Yakowitz & Pierre L'Ecuyer & Felisa Vázquez-Abad, 2000. "Global Stochastic Optimization with Low-Dispersion Point Sets," Operations Research, INFORMS, vol. 48(6), pages 939-950, December.
    8. Francis, Peter & Zhang, Guangming & Smilowitz, Karen, 2007. "Improved modeling and solution methods for the multi-resource routing problem," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1045-1059, August.

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