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Selection and multiple-comparison procedures for regenerative systems

Published: 03 December 2006 Publication History

Abstract

We propose two-stage methods for selection and multiple comparisons with the best (MCB) of steady-state performance measures of regenerative systems. We assume the systems being compared are simulated independently, and the methods presented are asymptotically valid as the confidence-interval width parameter shrinks and the first-stage run length grows at a rate that is at most the inverse of the square of the confidence-interval width parameter. When the first-stage run length is asymptotically negligible compared to the total run length, our procedures are asymptotically efficient. We provide an asymptotic comparison of our regenerative MCB procedures with those based on standardized time series (STS) methods in terms of mean and variance of total run length. We conclude that regenerative MCB methods are strictly better than STS MCB methods for any fixed number of batches, but the two become equivalent as the number of batches grows large.

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cover image ACM Conferences
WSC '06: Proceedings of the 38th conference on Winter simulation
December 2006
2429 pages
ISBN:1424405017

Sponsors

  • IIE: Institute of Industrial Engineers
  • ASA: American Statistical Association
  • IEICE ESS: Institute of Electronics, Information and Communication Engineers, Engineering Sciences Society
  • IEEE-CS\DATC: The IEEE Computer Society
  • SIGSIM: ACM Special Interest Group on Simulation and Modeling
  • NIST: National Institute of Standards and Technology
  • (SCS): The Society for Modeling and Simulation International
  • INFORMS-CS: Institute for Operations Research and the Management Sciences-College on Simulation

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Winter Simulation Conference

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Published: 03 December 2006

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WSC06
Sponsor:
  • IIE
  • ASA
  • IEICE ESS
  • IEEE-CS\DATC
  • SIGSIM
  • NIST
  • (SCS)
  • INFORMS-CS
WSC06: Winter Simulation Conference 2006
December 3 - 6, 2006
California, Monterey

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WSC '06 Paper Acceptance Rate 177 of 252 submissions, 70%;
Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

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