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.
['Halim Damerdji', 'Peter W. Glynn', 'Marvin K. Nakayama', 'James R. Wilson']
Selecting the best system in transient simulations with variances known