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Simple Procedures for Selecting the Best Simulated System When the Number of Alternatives is Large

Author

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  • Barry L. Nelson

    (Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, Illinois 60208-3119)

  • Julie Swann

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • David Goldsman

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

  • Wheyming Song

    (Department of Industrial Engineering, National Tsing Hua University, Hsinchu R.O.C., Taiwan)

Abstract

In this paper, we address the problem of finding the simulated system with the best (maximum or minimum) expected performance when the number of alternatives is finite, but large enough that ranking-and-selection (R&S) procedures may require too much computation to be practical. Our approach is to use the data provided by the first stage of sampling in an R&S procedure to screen out alternatives that are not competitive, and thereby avoid the (typically much larger) second-stage sample for these systems. Our procedures represent a compromise between standard R&S procedures---which are easy to implement, but can be computationally inefficient---and fully sequential procedures---which can be statistically efficient, but are more difficult to implement and depend on more restrictive assumptions. We present a general theory for constructing combined screening and indifference-zone selection procedures, several specific procedures and a portion of an extensive empirical evaluation.

Suggested Citation

  • Barry L. Nelson & Julie Swann & David Goldsman & Wheyming Song, 2001. "Simple Procedures for Selecting the Best Simulated System When the Number of Alternatives is Large," Operations Research, INFORMS, vol. 49(6), pages 950-963, December.
    • Handle: RePEc:inm:oropre:v:49:y:2001:i:6:p:950-963
    DOI: 10.1287/opre.49.6.950.10019
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    References listed on IDEAS

    as
    1. David W. Sullivan & James R. Wilson, 1989. "Restricted Subset Selection Procedures for Simulation," Operations Research, INFORMS, vol. 37(1), pages 52-71, February.
    2. David W. Sullivan & James R. Wilson, 1989. "Corrections to “Restricted Subset Selection Procedures for Simulation”," Operations Research, INFORMS, vol. 37(4), pages 673-673, August.
    3. Barry L. Nelson & David Goldsman, 2001. "Comparisons with a Standard in Simulation Experiments," Management Science, INFORMS, vol. 47(3), pages 449-463, March.
    4. Barry L. Nelson & Frank J. Matejcik, 1995. "Using Common Random Numbers for Indifference-Zone Selection and Multiple Comparisons in Simulation," Management Science, INFORMS, vol. 41(12), pages 1935-1945, December.
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