Efficient Simulation Budget Allocation for Ranking the Top m Designs
Joint Authors
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-18
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
We consider the problem of ranking the top m designs out of k alternatives.
Using the optimal computing budget allocation framework, we formulate this problem as that of maximizing the probability of correctly ranking the top m designs subject to the constraint of a fixed limited simulation budget.
We derive the convergence rate of the false ranking probability based on the large deviation theory.
The asymptotically optimal allocation rule is obtained by maximizing this convergence rate function.
To implement the simulation budget allocation rule, we suggest a heuristic sequential algorithm.
Numerical experiments are conducted to compare the effectiveness of the proposed simulation budget allocation rule.
The numerical results indicate that the proposed asymptotically optimal allocation rule performs the best comparing with other allocation rules.
American Psychological Association (APA)
Xiao, Hui& Lee, Loo Hay. 2014. Efficient Simulation Budget Allocation for Ranking the Top m Designs. Discrete Dynamics in Nature and Society،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-453571
Modern Language Association (MLA)
Xiao, Hui& Lee, Loo Hay. Efficient Simulation Budget Allocation for Ranking the Top m Designs. Discrete Dynamics in Nature and Society No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-453571
American Medical Association (AMA)
Xiao, Hui& Lee, Loo Hay. Efficient Simulation Budget Allocation for Ranking the Top m Designs. Discrete Dynamics in Nature and Society. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-453571
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-453571