Selecting the best system when systems are revealed sequentially

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review

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Original languageEnglish
Pages (from-to)723-734
Journal / PublicationIIE Transactions (Institute of Industrial Engineers)
Issue number7
Publication statusPublished - Jul 2007
Externally publishedYes


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.

Research Area(s)

  • Optimization via simulation, Ranking and selection, System design