Improved beluga whale optimization for solving the simulation optimization problems with stochastic constraints
Simulation optimization problems with stochastic constraints are optimization problems with deterministic cost functions subject to stochastic constraints. Solving the considered problem by traditional optimization approaches is time-consuming if the search space is large. In this work, an approach...
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ftchaoyanguniv:oai:localhost:310901800/41716 2023-06-11T04:10:37+02:00 Improved beluga whale optimization for solving the simulation optimization problems with stochastic constraints 洪士程 Horng, Shih-Cheng Lin, Shieh-Shing 資訊工程系 2023-04 2845824 bytes application/pdf http://ir.lib.cyut.edu.tw:8080/handle/310901800/41716 http://ir.lib.cyut.edu.tw:8080/bitstream/310901800/41716/2/mathematics-11-01854-v2.pdf en_US eng MDPI Mathematics 1(8), 1854 2227-7390 http://ir.lib.cyut.edu.tw:8080/handle/310901800/41716 http://ir.lib.cyut.edu.tw:8080/bitstream/310901800/41716/2/mathematics-11-01854-v2.pdf beluga whale optimization ordinal optimization polynomial chaos expansion optimal computational effort allocation emergency department healthcare average waiting time article 2023 ftchaoyanguniv 2023-05-28T18:03:17Z Simulation optimization problems with stochastic constraints are optimization problems with deterministic cost functions subject to stochastic constraints. Solving the considered problem by traditional optimization approaches is time-consuming if the search space is large. In this work, an approach integration of beluga whale optimization and ordinal optimization is presented to resolve the considered problem in a relatively short time frame. The proposed approach is composed of three levels: emulator, diversification, and intensification. Firstly, the polynomial chaos expansion is treated as an emulator to evaluate a design. Secondly, the improved beluga whale optimization is proposed to seek N candidates from the whole search space. Eventually, the advanced optimal computational effort allocation is adopted to determine a superior design from the N candidates. The proposed approach is utilized to seek the optimal number of service providers for minimizing staffing costs while delivering a specific level of care in emergency department healthcare. A practical example of an emergency department with six cases is used to verify the proposed approach. The CPU time consumes less than one minute for six cases, which demonstrates that the proposed approach can meet the requirement of real-time application. In addition, the proposed approach is compared to five heuristic methods. Empirical tests indicate the efficiency and robustness of the proposed approach. Article in Journal/Newspaper Beluga Beluga whale Beluga* Chaoyang University of Technology Institutional Repository (CYUTIR) |
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Chaoyang University of Technology Institutional Repository (CYUTIR) |
op_collection_id |
ftchaoyanguniv |
language |
English |
topic |
beluga whale optimization ordinal optimization polynomial chaos expansion optimal computational effort allocation emergency department healthcare average waiting time |
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beluga whale optimization ordinal optimization polynomial chaos expansion optimal computational effort allocation emergency department healthcare average waiting time 洪士程 Horng, Shih-Cheng Lin, Shieh-Shing Improved beluga whale optimization for solving the simulation optimization problems with stochastic constraints |
topic_facet |
beluga whale optimization ordinal optimization polynomial chaos expansion optimal computational effort allocation emergency department healthcare average waiting time |
description |
Simulation optimization problems with stochastic constraints are optimization problems with deterministic cost functions subject to stochastic constraints. Solving the considered problem by traditional optimization approaches is time-consuming if the search space is large. In this work, an approach integration of beluga whale optimization and ordinal optimization is presented to resolve the considered problem in a relatively short time frame. The proposed approach is composed of three levels: emulator, diversification, and intensification. Firstly, the polynomial chaos expansion is treated as an emulator to evaluate a design. Secondly, the improved beluga whale optimization is proposed to seek N candidates from the whole search space. Eventually, the advanced optimal computational effort allocation is adopted to determine a superior design from the N candidates. The proposed approach is utilized to seek the optimal number of service providers for minimizing staffing costs while delivering a specific level of care in emergency department healthcare. A practical example of an emergency department with six cases is used to verify the proposed approach. The CPU time consumes less than one minute for six cases, which demonstrates that the proposed approach can meet the requirement of real-time application. In addition, the proposed approach is compared to five heuristic methods. Empirical tests indicate the efficiency and robustness of the proposed approach. |
author2 |
資訊工程系 |
format |
Article in Journal/Newspaper |
author |
洪士程 Horng, Shih-Cheng Lin, Shieh-Shing |
author_facet |
洪士程 Horng, Shih-Cheng Lin, Shieh-Shing |
author_sort |
洪士程 |
title |
Improved beluga whale optimization for solving the simulation optimization problems with stochastic constraints |
title_short |
Improved beluga whale optimization for solving the simulation optimization problems with stochastic constraints |
title_full |
Improved beluga whale optimization for solving the simulation optimization problems with stochastic constraints |
title_fullStr |
Improved beluga whale optimization for solving the simulation optimization problems with stochastic constraints |
title_full_unstemmed |
Improved beluga whale optimization for solving the simulation optimization problems with stochastic constraints |
title_sort |
improved beluga whale optimization for solving the simulation optimization problems with stochastic constraints |
publisher |
MDPI |
publishDate |
2023 |
url |
http://ir.lib.cyut.edu.tw:8080/handle/310901800/41716 http://ir.lib.cyut.edu.tw:8080/bitstream/310901800/41716/2/mathematics-11-01854-v2.pdf |
genre |
Beluga Beluga whale Beluga* |
genre_facet |
Beluga Beluga whale Beluga* |
op_relation |
Mathematics 1(8), 1854 2227-7390 http://ir.lib.cyut.edu.tw:8080/handle/310901800/41716 http://ir.lib.cyut.edu.tw:8080/bitstream/310901800/41716/2/mathematics-11-01854-v2.pdf |
_version_ |
1768385142332588032 |