Optimization using common random numbers, control variates and multiple comparisons with the best

Wei Ning Yang*, Barry L. Nelson

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

Consideration is given to the problem of determining the best of a finite number of system designs by simulation experimentation when the criterion of interest is the maximum or minimum expected performance. This is a special case of the general problem of optimization via simulation. The proposed method is based on multiple comparisons with the best (MCB), described by J. C. Hsu (An. Stat., vol. 12, pp. 1136-1144, 1984), which constructs simultaneous interval estimates for the difference between the expected performance of each system design and the best of the other designs. A refinement of Hsu's procedure is proposed using two variance reduction techniques, common random numbers and control variates, that are particularly useful in simulation experiments. It is shown that the proposed procedure is better than standard MCB in the sense that it is more sensitive to differences in expected performance.

Original languageEnglish (US)
Pages (from-to)444-449
Number of pages6
JournalWinter Simulation Conference Proceedings
DOIs
StatePublished - 1989
Event1989 Winter Simulation Conference Proceedings - WSC '89 - Washington, DC, USA
Duration: Dec 4 1989Dec 6 1989

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Safety, Risk, Reliability and Quality
  • Chemical Health and Safety
  • Applied Mathematics

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