Selecting Small Quantiles

Abstract

Ranking and selection (R&S) techniques are statistical methods developed to select the best system, or a subset of systems, from among a set of alternative system designs. R&S via simulation is particularly appealing as it combines the modeling flexibility of simulation with the efficiency of statistical techniques for effective decision making. The overwhelming majority of the R&S research, however, focuses on the expected performance of competing designs. Alternatively, quantiles, which provide additional information about the distribution of the performance measure of interest, may serve as better risk measures than the usual expected value. In stochastic systems, quantiles indicate the level of system performance that can be delivered with a specified probability. In this paper, we address the problem of ranking and selection based on quantiles. In particular, we formulate the problem and characterize the optimal budget allocation scheme using large deviations theory.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2010
Accession Number
ADA554315

Entities

People

  • Enver Yucesan
  • Raghu Pasupathy
  • Roberto Szechtman

Organizations

  • Virginia Tech

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  • Biomedical

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