Selecting the best system when systems are revealed sequentially

L. Jeff Hong, Barry L. Nelson*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

Statistical Ranking and Selection (R&S) is a collection of experiment design and analysis techniques for selecting the system 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. All existing procedures assume that the set of alternatives is available at the beginning of the experiment. In many situations, however, the alternatives are revealed (generated) sequentially during the experiment. We introduce procedures that are capable of selecting the best alternative in these situations and provide the desired statistical guarantees.

Original languageEnglish (US)
Pages (from-to)723-734
Number of pages12
JournalIIE Transactions (Institute of Industrial Engineers)
Volume39
Issue number7
DOIs
StatePublished - Jul 2007

Keywords

  • Optimization via simulation
  • Ranking and selection
  • System design

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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