Selecting the best system in transient simulations with variances known

Authors:
Halim Damerdji;Peter W. Glynn;Marvin K. Nakayama;James R. Wilson
Affiliations:
Department of Industrial Engineering, North Carolina State University Raleigh, NC;Department of Operations Research, Stanford University, Stanford, CA;Department of Computer and Information Science, New Jersey Institute of Technology, Newark, NJ;Department of Industrial Engineering, North Carolina State University, Raleigh, NC
Venue:
WSC '96 Proceedings of the 28th conference on Winter simulation
Year:
1996

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Abstract

Selection of the best system among k different systems is investigated. This selection is based upon the results of finite-horizon simulations. Since the distribution of the output of a transient simulation is typically unknown, it follows that this problem is that of selection of the best population (best according to some measure) among k different populations, where observations within each population are independent, and identically distributed according to some general (unknown) distribution. In this work in progress, it is assumed that the population variances are known. A natural single-stage sampling procedure is presented. Under Bechbofer's indifference zone approach, this procedure is asymptotically valid.