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A note on the subset selection for simulation optimization

Published: 06 December 2015 Publication History

Abstract

In this paper, we consider the problem of selecting an optimal subset from a finite set of simulated designs. Using the optimal computing budget allocation (OCBA) framework, we formulate the problem as that of maximizing the probability of correctly selecting the top m designs subject to a constraint on the total number of samples available. For an approximation of the probability of correct selection, we derive an asymptotically optimal subset selection procedure that is easy to implement. More importantly, we provide some useful insights on characterizing an efficient subset selection rule and how it can be achieved by adjusting the budgets allocated to the optimal and non-optimal subsets.

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Cited By

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  • (2021)Dynamic sampling policy for subset selectionProceedings of the Winter Simulation Conference10.5555/3522802.3522957(1-12)Online publication date: 13-Dec-2021
  • (2018)Practical considerations in selecting the best set of simulated systemsProceedings of the 2018 Winter Simulation Conference10.5555/3320516.3320779(2191-2200)Online publication date: 9-Dec-2018

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cover image ACM Conferences
WSC '15: Proceedings of the 2015 Winter Simulation Conference
December 2015
4051 pages
ISBN:9781467397414

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IEEE Press

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Published: 06 December 2015

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WSC '15
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WSC '15: Winter Simulation Conference
December 6 - 9, 2015
California, Huntington Beach

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WSC '15 Paper Acceptance Rate 202 of 296 submissions, 68%;
Overall Acceptance Rate 3,413 of 5,075 submissions, 67%

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View all
  • (2021)Dynamic sampling policy for subset selectionProceedings of the Winter Simulation Conference10.5555/3522802.3522957(1-12)Online publication date: 13-Dec-2021
  • (2018)Practical considerations in selecting the best set of simulated systemsProceedings of the 2018 Winter Simulation Conference10.5555/3320516.3320779(2191-2200)Online publication date: 9-Dec-2018

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