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Adaptive simulation budget allocation for determining the best design

  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We consider the problem of allocating a given simulation budget among a set of design alternatives in order to maximize the probability of correct selection. Prior work has focused on deriving static rules that predetermine the number of simulation replications to be allocated to each design. In contrast, we formulate the problem as a Markov decision process (MDP) and propose a dynamic myopic scheme to adaptively allocate simulation samples based on current estimates of the means and variances of the design alternatives. We provide numerical examples to illustrate the performance of the proposed dynamic allocation rule.

Original languageEnglish
Title of host publicationProceedings of the 2013 Winter Simulation Conference - Simulation
Subtitle of host publicationMaking Decisions in a Complex World, WSC 2013
Pages888-897
Number of pages10
DOIs
StatePublished - 2013
Event2013 43rd Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013 - Washington, DC, United States
Duration: Dec 8 2013Dec 11 2013

Publication series

NameProceedings of the 2013 Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013

Conference

Conference2013 43rd Winter Simulation Conference - Simulation: Making Decisions in a Complex World, WSC 2013
Country/TerritoryUnited States
CityWashington, DC
Period12/8/1312/11/13

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