Simple procedures for selecting the best simulated system when the number of alternatives is large

Barry L. Nelson*, Julie Swann, David Goldsman, Wheyming Song

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

195 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)950-963
Number of pages14
JournalOperations Research
Volume49
Issue number6
DOIs
StatePublished - 2001

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research

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