Selecting the best simulated system with weighted control-variate estimators

Authors:
Shing Chih Tsai
Affiliations:
Department of Industrial and Information Management, National Cheng Kung University, No. 1, University Road, Tainan City, Taiwan
Venue:
Mathematics and Computers in Simulation
Year:
2011

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Abstract

Ranking and selection (R&S) procedures have been considered an effective tool to solve simulation optimization problems with a discrete and finite decision space. Control variate (CV) is a variance reduction technique that requires no intervention in the way the simulation experiment is performed, and the least-squares regression package needed to implement CV is readily available. In this paper we propose two provably valid selection procedures that employ weighted CV estimators in different ways. Both procedures are guaranteed to select the best system with a prespecified confidence level. Empirical results and simple analyses are performed to compare the efficiency of our new procedures with some existing procedures.