An indifference-zone selection procedure with minimum switching and sequential sampling

L. Jeff Hong*, Barry L Nelson

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

Statistical ranking and selection (R&S) is a collection of experiment design and analysis techniques for selecting the "population" with the largest or smallest mean performance from among a finite set of alternatives. R&S procedures have received considerable research attention in the stochastic simulation community, and they have been incorporated in commercial simulation software. One of the ways that R&S procedures are evaluated and compared is via the expected number of samples (often replications) that must be generated to reach a decision. In this paper we argue that sampling cost alone does not adequately characterize the efficiency of ranking-and-selection procedures, and we introduce a new sequential procedure that provides the same statistical guarantees as existing procedures while reducing the expected total cost of application.

Original languageEnglish (US)
Pages (from-to)474-480
Number of pages7
JournalWinter Simulation Conference Proceedings
Volume1
StatePublished - Dec 1 2003
EventProceedings of the 2003 Winter Simulation Conference: Driving Innovation - New Orleans, LA, United States
Duration: Dec 7 2003Dec 10 2003

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Safety, Risk, Reliability and Quality
  • Applied Mathematics
  • Chemical Health and Safety

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