Fixed-width multiple-comparison procedures using common random numbers for steady-state simulations

Document Type

Article

Publication Date

11-1-2007

Abstract

Suppose that there are k ≥ 2 different systems (i.e., stochastic processes), where each system has an unknown steady-state mean performance. We consider the problem of running a two-stage simulation using common random numbers to construct fixed-width confidence intervals for two multiple-comparison problems. Under the assumptions that the stochastic processes representing the simulation output of the different systems satisfy a functional central limit theorem and that the asymptotic covariance matrix satisfies a condition known as sphericity, we prove that our confidence intervals are asymptotically valid (as the desired half-width of the confidence intervals tend to zero). We develop both absolute- and relative-width confidence intervals. Empirical results are presented indicating the procedures' robustness to violations of the sphericity assumption. © 2006 Elsevier B.V. All rights reserved.

Identifier

34248215130 (Scopus)

Publication Title

European Journal of Operational Research

External Full Text Location

https://doi.org/10.1016/j.ejor.2006.09.045

ISSN

03772217

First Page

1330

Last Page

1349

Issue

3

Volume

182

Grant

DMI-9624469

Fund Ref

National Science Foundation

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