A Fully Sequential Procedure for Indifference-Zone Selection in Simulation

Seong Hee Kim*, Barry L Nelson

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

240 Scopus citations

Abstract

We present procedures for selecting the best or near-best of a finite number of simulated systems when best is defined by maximum or minimum expected performance. The procedures are appropriate when it is possible to repeatedly obtain small, incremental samples from each simulated system. The goal of such a sequential procedure is to eliminate, at an early stage of experimentation, those simulated systems that are apparently inferior, and thereby reduce the overall computational effort required to find the best. The procedures we present accommodate unequal variances across systems and the use of common random numbers. However, they are based on the assumption of normally distributed data, so we analyze the impact of batching (to achieve approximate normality or independence) on the performance of the procedures. Comparisons with some existing indifference-zone procedures are also provided.

Original languageEnglish (US)
Pages (from-to)251-273
Number of pages23
JournalACM Transactions on Modeling and Computer Simulation
Volume11
Issue number3
DOIs
StatePublished - Jul 1 2001

Keywords

  • Multiple comparisons
  • Output analysis
  • Ranking and selection
  • Variance reduction

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation

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