Discrete-event simulation optimization using ranking, selection, and multiple comparison procedures: A survey
This paper presents a Bonferroni procedure for selecting the alternative with the largest mean when the variances are unknown and unequal and correlation is induced among the observations for each alternative by common random numbers. Simulation results show that the Bonferroni procedure is more efficient than Dudewicz and Dalal's procedure when the percentage of variance reduction is high.
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