Efficient Simulation Budget Allocation With Bound Information

This paper proposes a bound-based simulation budget allocation (BSBA) procedure for solving ranking and selection (R&S) problems in simulation optimization. For many practical applications, strict bounds on system performances can be obtained through empirical and theoretical approaches. These b...

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Main Authors: Li, Haidong, Xu, Xiaoyun, Zhao, Yaping
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Published: Archīum Ateneo 2019
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Online Access:https://archium.ateneo.edu/gsb-pubs/3
https://ieeexplore.ieee.org/abstract/document/8675337?casa_token=1B5V8SdZvwYAAAAA:azZh4w_1RqMdeCy4F7opiSxV0r8aSZiBhs_ZWdYuugSbDTe96OasEUlRSG2tqld5SQVTEkSbZbw
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Institution: Ateneo De Manila University
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spelling ph-ateneo-arc.gsb-pubs-10022022-03-22T08:25:23Z Efficient Simulation Budget Allocation With Bound Information Li, Haidong Xu, Xiaoyun Zhao, Yaping This paper proposes a bound-based simulation budget allocation (BSBA) procedure for solving ranking and selection (R&S) problems in simulation optimization. For many practical applications, strict bounds on system performances can be obtained through empirical and theoretical approaches. These bounds provide additional information which may help solve R&S problems. In this paper, a new method of objective function estimation is proposed using both bound information and simulation outputs. This new estimation method is demonstrated to be particularly effective. To solve R&S problems, several asymptotic optimal allocation rules are also derived. Using these allocation rules, a BSBA procedure is proposed to achieve high efficiency in identifying the best design. Numerical experiments are provided to examine the performance of the proposed BSBA procedure. The computational results show that BSBA outperforms three compared allocation procedures, especially when bounds are tight or the simulation budget is small. 2019-01-01T08:00:00Z text https://archium.ateneo.edu/gsb-pubs/3 https://ieeexplore.ieee.org/abstract/document/8675337?casa_token=1B5V8SdZvwYAAAAA:azZh4w_1RqMdeCy4F7opiSxV0r8aSZiBhs_ZWdYuugSbDTe96OasEUlRSG2tqld5SQVTEkSbZbw Graduate School of Business Faculty Publications Archīum Ateneo Risk Assesment and Reduction Creativity Innovation Culture Business Administration, Management, and Operations
institution Ateneo De Manila University
building Ateneo De Manila University Library
continent Asia
country Philippines
Philippines
content_provider Ateneo De Manila University Library
collection archium.Ateneo Institutional Repository
topic Risk Assesment and Reduction
Creativity
Innovation
Culture
Business Administration, Management, and Operations
spellingShingle Risk Assesment and Reduction
Creativity
Innovation
Culture
Business Administration, Management, and Operations
Li, Haidong
Xu, Xiaoyun
Zhao, Yaping
Efficient Simulation Budget Allocation With Bound Information
description This paper proposes a bound-based simulation budget allocation (BSBA) procedure for solving ranking and selection (R&S) problems in simulation optimization. For many practical applications, strict bounds on system performances can be obtained through empirical and theoretical approaches. These bounds provide additional information which may help solve R&S problems. In this paper, a new method of objective function estimation is proposed using both bound information and simulation outputs. This new estimation method is demonstrated to be particularly effective. To solve R&S problems, several asymptotic optimal allocation rules are also derived. Using these allocation rules, a BSBA procedure is proposed to achieve high efficiency in identifying the best design. Numerical experiments are provided to examine the performance of the proposed BSBA procedure. The computational results show that BSBA outperforms three compared allocation procedures, especially when bounds are tight or the simulation budget is small.
format text
author Li, Haidong
Xu, Xiaoyun
Zhao, Yaping
author_facet Li, Haidong
Xu, Xiaoyun
Zhao, Yaping
author_sort Li, Haidong
title Efficient Simulation Budget Allocation With Bound Information
title_short Efficient Simulation Budget Allocation With Bound Information
title_full Efficient Simulation Budget Allocation With Bound Information
title_fullStr Efficient Simulation Budget Allocation With Bound Information
title_full_unstemmed Efficient Simulation Budget Allocation With Bound Information
title_sort efficient simulation budget allocation with bound information
publisher Archīum Ateneo
publishDate 2019
url https://archium.ateneo.edu/gsb-pubs/3
https://ieeexplore.ieee.org/abstract/document/8675337?casa_token=1B5V8SdZvwYAAAAA:azZh4w_1RqMdeCy4F7opiSxV0r8aSZiBhs_ZWdYuugSbDTe96OasEUlRSG2tqld5SQVTEkSbZbw
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