Two Scenario-Based Heuristics for Stochastic Shift Design Problem with Task-Based Demand
In this paper, we propose a deterministic shift design model with task-based demand and give the corresponding stochastic version with a probability constraint such that the shift plan designed is staffed with the workforce with a certain probability of performing all given tasks. Since we currently...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-09-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/18/10070 |
| _version_ | 1797581423319711744 |
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| author | Zhiying Wu Qingxin Chen Ning Mao Guoning Xu |
| author_facet | Zhiying Wu Qingxin Chen Ning Mao Guoning Xu |
| author_sort | Zhiying Wu |
| collection | DOAJ |
| description | In this paper, we propose a deterministic shift design model with task-based demand and give the corresponding stochastic version with a probability constraint such that the shift plan designed is staffed with the workforce with a certain probability of performing all given tasks. Since we currently find no suitable methods for solving this stochastic model from the literature related to solving stochastic shift design models, we developed a single-stage heuristic method based on statistics, whose main idea is to reduce the occurrence of manpower shortage by prolonging the resource occupation time of a task, but this leads to a serious waste of resources, which is common in solving resource allocation problems with uncertain durations. To reduce the cost of wastage, we also propose a two-stage heuristic approach that is a two-stage heuristic with an evolutionary strategy. The two heuristics show their effectiveness in solving the proposed stochastic model in numerical experiments, and the two-stage heuristic significantly outperforms the one-stage heuristic in cost optimization and solution time stability. |
| first_indexed | 2024-03-10T23:05:14Z |
| format | Article |
| id | doaj.art-2eb287d738c14e0c844b39211ac054e5 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T23:05:14Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-2eb287d738c14e0c844b39211ac054e52023-11-19T09:22:36ZengMDPI AGApplied Sciences2076-34172023-09-0113181007010.3390/app131810070Two Scenario-Based Heuristics for Stochastic Shift Design Problem with Task-Based DemandZhiying Wu0Qingxin Chen1Ning Mao2Guoning Xu3Key Laboratory of Computer Integrated Manufacturing System, Guangdong University of Technology, Guangzhou 510006, ChinaKey Laboratory of Computer Integrated Manufacturing System, Guangdong University of Technology, Guangzhou 510006, ChinaKey Laboratory of Computer Integrated Manufacturing System, Guangdong University of Technology, Guangzhou 510006, ChinaKey Laboratory of Computer Integrated Manufacturing System, Guangdong University of Technology, Guangzhou 510006, ChinaIn this paper, we propose a deterministic shift design model with task-based demand and give the corresponding stochastic version with a probability constraint such that the shift plan designed is staffed with the workforce with a certain probability of performing all given tasks. Since we currently find no suitable methods for solving this stochastic model from the literature related to solving stochastic shift design models, we developed a single-stage heuristic method based on statistics, whose main idea is to reduce the occurrence of manpower shortage by prolonging the resource occupation time of a task, but this leads to a serious waste of resources, which is common in solving resource allocation problems with uncertain durations. To reduce the cost of wastage, we also propose a two-stage heuristic approach that is a two-stage heuristic with an evolutionary strategy. The two heuristics show their effectiveness in solving the proposed stochastic model in numerical experiments, and the two-stage heuristic significantly outperforms the one-stage heuristic in cost optimization and solution time stability.https://www.mdpi.com/2076-3417/13/18/10070shift designtask-based demandprobability constraintheuristic |
| spellingShingle | Zhiying Wu Qingxin Chen Ning Mao Guoning Xu Two Scenario-Based Heuristics for Stochastic Shift Design Problem with Task-Based Demand Applied Sciences shift design task-based demand probability constraint heuristic |
| title | Two Scenario-Based Heuristics for Stochastic Shift Design Problem with Task-Based Demand |
| title_full | Two Scenario-Based Heuristics for Stochastic Shift Design Problem with Task-Based Demand |
| title_fullStr | Two Scenario-Based Heuristics for Stochastic Shift Design Problem with Task-Based Demand |
| title_full_unstemmed | Two Scenario-Based Heuristics for Stochastic Shift Design Problem with Task-Based Demand |
| title_short | Two Scenario-Based Heuristics for Stochastic Shift Design Problem with Task-Based Demand |
| title_sort | two scenario based heuristics for stochastic shift design problem with task based demand |
| topic | shift design task-based demand probability constraint heuristic |
| url | https://www.mdpi.com/2076-3417/13/18/10070 |
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