A Simulation Budget Allocation Procedure for Enhancing the Efficiency of Optimal Subset Selection

Selecting the optimal subset is highly beneficial to numerous developments in simulation optimization. This paper studies the problem of maximizing the probability of correctly selecting the top- m designs out of k designs under a computing budget constraint. We develop a new procedure which is more...

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Bibliographic Details
Published in:IEEE transactions on automatic control 2016-01, Vol.61 (1), p.62-75
Main Authors: Zhang, Si, Lee, Loo Hay, Chew, Ek Peng, Xu, Jie, Chen, Chun-Hung
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Approximation methods
Computational modeling
Convergence
discrete-event systems
Optimization
random systems
Resource management
stochastic simulation
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Summary:Selecting the optimal subset is highly beneficial to numerous developments in simulation optimization. This paper studies the problem of maximizing the probability of correctly selecting the top- m designs out of k designs under a computing budget constraint. We develop a new procedure which is more efficient and robust than currently existing procedures in the literature. We also provide an analysis on its asymptotic convergence rate. Based on this analysis, we show that our new procedure achieves a higher convergence rate than other procedures under certain conditions. Numerical testing supports our analytical analysis and shows that the new procedure is significantly more efficient and robust.
ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2015.2423832