research-article
Authors: Xiao Jin, Yichi Shen, Loo Hay Lee, Ek Peng Chew, Christine A. Shoemaker
WSC '20: Proceedings of the Winter Simulation Conference
Pages 2996 - 3007
Published: 13 May 2021 Publication History
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Abstract
We propose a new method for solving continuous contextual simulation optimization with a single observation. By adopting the estimation on the large deviation rate in the contextual ranking and selection problem, we transfer the old theorem to the continuous setting using a shrinking ball inspired construct. Through the estimation of the rate, the new method is expected to achieve the optimal performance in this new problem setting. Brief numerical experiments are conducted and show significant advantages of our method against the uniform sampling scheme.
References
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Gao, S., C. Li, and J. Du. 2019. "Rate Analysis for Offline Simulation Online Application". In Proceedings of the 2019 Winter Simulation Conference, edited by S. L.-M. M. R. C. S. P. H. N. Mustafee, K.-H.G. Bae and Y.-J. Son, 3468--3479. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc.
Digital Library
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Glynn, P., and S. Juneja. 2004. "A Large Deviations Perspective on Ordinal Optimization". In Proceedings of the 2004 Winter Simulation Conference, edited by J. S. S. R. G. Ingalls, M. D. Rossetti and B. A. Peters, Volume 1, 585. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc.
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Jin, X., H. Li, and L. H. Lee. 2019. "Optimal Budget Allocation in Simulation Analytics". In 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE), 178--182. Institute of Electrical and Electronics Engineers, Inc.
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Kiatsupaibul, S., R. L. Smith, and Z. B. Zabinsky. 2018. "Single Observation Adaptive Search for Continuous Simulation Optimization". Operations Research 66(6):1713--1727.
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Linz, D. D., Z. B. Zabinsky, S. Kiatsupaibul, and R. L. Smith. 2017. "A Computational Comparison of Simulation Optimization Methods Using Single Observations within a Shrinking Ball on Noisy Black-box Functions with Mixed Integer and Continuous Domains". In Proceedings of the 2017 Winter Simulation Conference, edited by G. Z. N. M. G. W. W. K. V. Chan, A. D'Ambrogio and E. Page, 2045--2056. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc.
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Shen, H., L. J. Hong, and X. Zhang. 2017. "Ranking and Selection with Covariates". In Proceedings of the 2017 Winter Simulation Conference, edited by G. Z. N. M. G. W. W. K. V. Chan, A. D'Ambrogio and E. Page, 2137--2148. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc.
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Cited By
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- Shen YShoemaker C(2020)Global optimization for noisy expensive black-box multi-modal functions via radial basis function surrogateProceedings of the Winter Simulation Conference10.5555/3466184.3466531(3020-3031)Online publication date: 14-Dec-2020
https://dl.acm.org/doi/10.5555/3466184.3466531
Index Terms
A hybrid of shrinking ball method and optimal large deviation rate estimation in continuous contextual simulation optimization with single observation
Computing methodologies
Modeling and simulation
Mathematics of computing
Mathematical analysis
Mathematical optimization
Theory of computation
Design and analysis of algorithms
Mathematical optimization
Index terms have been assigned to the content through auto-classification.
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Published In
WSC '20: Proceedings of the Winter Simulation Conference
December 2020
3329 pages
ISBN:9781728194998
Sponsors
- SIGSIM: ACM Special Interest Group on Simulation and Modeling
In-Cooperation
- SCS: Society for Computer Simulation
Publisher
IEEE Press
Publication History
Published: 13 May 2021
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WSC '20
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Overall Acceptance Rate 3,413 of 5,075 submissions, 67%
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Cited By
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- Shen YShoemaker C(2020)Global optimization for noisy expensive black-box multi-modal functions via radial basis function surrogateProceedings of the Winter Simulation Conference10.5555/3466184.3466531(3020-3031)Online publication date: 14-Dec-2020
https://dl.acm.org/doi/10.5555/3466184.3466531
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