A restricted multinomial hybrid selection procedure

Authors:
Hélcio Vieira, Jr.;Susan M. Sanchez;Paul J. Sanchez;Karl Heinz Kienitz;Mischel Carmen Neyra Belderrain
Affiliations:
Technological Institute of Aeronautics, SP, Brazil;Naval Postgraduate School, CA, USA;Naval Postgraduate School, CA, USA;Technological Institute of Aeronautics, SP, Brazil;Technological Institute of Aeronautics, SP, Brazil
Venue:
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Year:
2014

Citing 3
Cited 0

Using common random numbers for indifference-zone selection and multiple comparisons in simulation

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On selecting the best of k systems: an expository survey of subset-selection multinomial procedures

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On the minimization of multinomial tails and the Gupta-Nagel conjecture

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Abstract

Analysts using simulation models often must assess a large number of alternatives in order to determine which are most effective. If effectiveness corresponds to the likelihood of yielding the best outcome, this becomes a multinomial selection problem. Unfortunately, existing procedures were developed primarily for evaluating small sets of alternatives, so parameters required to implement them may not be readily available or the sampling costs may be prohibitive when a large number of alternatives are present. We propose a truncated, sequential multinomial subset selection procedure that restricts the maximum subset size. Numerical comparisons show that our procedure can be much more efficient than the leading unrestricted procedure. Our procedure requires only one calculated parameter rather than four. We provide extensive tables for cases involving large numbers of alternatives.