Selecting the best system in steady-state simulations using batch means

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Abstract

Suppose that we want to compare k different systems, where μi denotes the steady-state mean performance of system i. Our goal is to use simulation to pick the 'best' system (i.e., the one with the largest or smallest steady-state mean). To do this, we present some two-stage procedures based on the method of batch means. Our procedures also construct multiple-comparisons-with-the-best (MCB) confidence intervals for μi - maxj≠i μj, i = 1,...,k. Under the assumption of an indifference zone of (absolute or relative) width δ, we can show that asymptotically (as δ → 0 with the size of the batches proportional to 1/δ2), the joint probability of correctly selecting the best system and of the MCB confidence intervals simultaneously containing μi - maxj≠i μj, i = 1,...,k, is at least 1 - α, where α is prespecified by the user.

Original languageEnglish (US)
Pages (from-to)362-366
Number of pages5
JournalWinter Simulation Conference Proceedings
DOIs
StatePublished - 1995
EventProceedings of the 1995 Winter Simulation Conference, WSC'95 - Arlington, VA, USA
Duration: Dec 3 1995Dec 6 1995

All Science Journal Classification (ASJC) codes

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

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