Using quantiles in ranking and selection procedures

Jennifer Bekki, John Fowler, Gerald T. Mackulak, Barry L. Nelson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

A useful performance measure on which to compare manufacturing systems is a quantile of the cycle time distribution. Unfortunately, aside from order statistic estimates, which can require significant data storage, the distribution of quantile estimates has not been shown to be normally distributed, violating a common assumption amongst ranking-and-selection (R&S) procedures. To address this, we provide empirical evidence supporting an approach using the mean of a group of quantile estimates as the comparison measure. The approach is detailed and illustrated through experimentation on four M/M/1 queues in which the 0.9 cycle-time quantile is the performance measure. Results in terms of simulation effort and accuracy are reported and compared to results obtained using the macro-replications approach for inducing normality as well as to results obtained by applying R&S procedures to quantile estimates directly. The suggested procedure is shown to provide significant savings in simulation effort while sacrificing very little in accuracy.

Original languageEnglish (US)
Title of host publicationProceedings of the 2007 Winter Simulation Conference, WSC
Pages1722-1728
Number of pages7
DOIs
StatePublished - 2007
Event2007 Winter Simulation Conference, WSC - Washington, DC, United States
Duration: Dec 9 2007Dec 12 2007

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736

Other

Other2007 Winter Simulation Conference, WSC
Country/TerritoryUnited States
CityWashington, DC
Period12/9/0712/12/07

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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