Optimising work-sharing in disassembly line balancing problems: a multi-cycle strategy.
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| Title: | Optimising work-sharing in disassembly line balancing problems: a multi-cycle strategy. |
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| Authors: | Li, Min1 (AUTHOR), Zhou, Binghai1 (AUTHOR) bhzhou@tongji.edu.cn |
| Source: | International Journal of Production Research. Sep2025, Vol. 63 Issue 18, p6827-6854. 28p. |
| Subjects: | Assembly line balancing, Work sharing, Engineering systems, Turnaround time, Algorithms, Resource allocation, Mixed integer linear programming, Optimization algorithms |
| Abstract: | To improve workload balance and reduce cycle time in disassembly line balancing problems, a multi-cycle work-sharing strategy that allows tasks to be reassigned across sub-cycles is proposed for the first time. While this strategy enhances disassembly efficiency, it also increases total resource demands, as different tasks may require distinct resources for effective execution. Therefore, to effectively address this challenge, a bi-objective integer linear programming model is established with the goal of minimising both overall cycle time and total resource count. The epsilon constraint method is then employed to obtain solutions for small-scale problems. For large-scale problems, a Double Deep Q-Network-based Hyper-Heuristic (DDQN-HH) algorithm is developed. This approach incorporates specialised encoding and decoding strategies, two state functions, and eight heuristic action rules to enhance its effectiveness. And comparative experiments using multi-objective evaluation metrics demonstrate the DDQN-HH algorithm's superiority over three other leading algorithms: the Deep Q-Network-based Hyper Heuristic (DQN-HH) algorithm, the Random, Greedy-based Hyper Heuristic (RG-HH) algorithm, and the Multi-objective Equilibrium Optimiser (MOEO) algorithm. Furthermore, the DDQN-HH's practical significance in addressing real-world engineering problems is validated through managerial applications. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 187749449 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Optimising work-sharing in disassembly line balancing problems: a multi-cycle strategy. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Li%2C+Min%22">Li, Min</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhou%2C+Binghai%22">Zhou, Binghai</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> bhzhou@tongji.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Sep2025, Vol. 63 Issue 18, p6827-6854. 28p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Assembly+line+balancing%22">Assembly line balancing</searchLink><br /><searchLink fieldCode="DE" term="%22Work+sharing%22">Work sharing</searchLink><br /><searchLink fieldCode="DE" term="%22Engineering+systems%22">Engineering systems</searchLink><br /><searchLink fieldCode="DE" term="%22Turnaround+time%22">Turnaround time</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Resource+allocation%22">Resource allocation</searchLink><br /><searchLink fieldCode="DE" term="%22Mixed+integer+linear+programming%22">Mixed integer linear programming</searchLink><br /><searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: To improve workload balance and reduce cycle time in disassembly line balancing problems, a multi-cycle work-sharing strategy that allows tasks to be reassigned across sub-cycles is proposed for the first time. While this strategy enhances disassembly efficiency, it also increases total resource demands, as different tasks may require distinct resources for effective execution. Therefore, to effectively address this challenge, a bi-objective integer linear programming model is established with the goal of minimising both overall cycle time and total resource count. The epsilon constraint method is then employed to obtain solutions for small-scale problems. For large-scale problems, a Double Deep Q-Network-based Hyper-Heuristic (DDQN-HH) algorithm is developed. This approach incorporates specialised encoding and decoding strategies, two state functions, and eight heuristic action rules to enhance its effectiveness. And comparative experiments using multi-objective evaluation metrics demonstrate the DDQN-HH algorithm's superiority over three other leading algorithms: the Deep Q-Network-based Hyper Heuristic (DQN-HH) algorithm, the Random, Greedy-based Hyper Heuristic (RG-HH) algorithm, and the Multi-objective Equilibrium Optimiser (MOEO) algorithm. Furthermore, the DDQN-HH's practical significance in addressing real-world engineering problems is validated through managerial applications. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/00207543.2025.2489041 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 28 StartPage: 6827 Subjects: – SubjectFull: Assembly line balancing Type: general – SubjectFull: Work sharing Type: general – SubjectFull: Engineering systems Type: general – SubjectFull: Turnaround time Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Resource allocation Type: general – SubjectFull: Mixed integer linear programming Type: general – SubjectFull: Optimization algorithms Type: general Titles: – TitleFull: Optimising work-sharing in disassembly line balancing problems: a multi-cycle strategy. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Li, Min – PersonEntity: Name: NameFull: Zhou, Binghai IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 09 Text: Sep2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 00207543 Numbering: – Type: volume Value: 63 – Type: issue Value: 18 Titles: – TitleFull: International Journal of Production Research Type: main |
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