Finding the best in the presence of a stochastic constraint

Authors:
Sigrún Andradóttir;David Goldsman;Seong-Hee Kim
Affiliations:
Georgia Institute of Technology, Atlanta, GA;Georgia Institute of Technology, Atlanta, GA;Georgia Institute of Technology, Atlanta, GA
Venue:
WSC '05 Proceedings of the 37th conference on Winter simulation
Year:
2005

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Abstract

Our problem is that of finding the best system---i.e., the system with the largest or smallest primary performance measure---among a finite number of simulated systems in the presence of a stochastic constraint on a secondary performance measure. In order to solve this problem, we first find a set that contains only feasible or near-feasible systems (Phase I) and then choose the best among those systems in the set (Phase II). We present a statistically valid procedure for Phase I and then propose another procedure that performs Phases I and II sequentially to find the best feasible system. Finally, we provide some experimental results for the second procedure.