Joint optimisation of product family configuration and supply chain resilience.
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| Title: | Joint optimisation of product family configuration and supply chain resilience. |
|---|---|
| Authors: | Zeng, Ming1 (AUTHOR), Ye, Yangyang1 (AUTHOR), Luo, Xinggang1,2 (AUTHOR) xgluo@mail.neu.edu.cn, Chen, Wenchong1,2 (AUTHOR), Zhang, Zhongliang1,2 (AUTHOR), Zeng, Ruochen3 (AUTHOR) rczeng@shu.edu.cn |
| Source: | International Journal of Production Research. Jun2025, Vol. 63 Issue 11, p4163-4179. 17p. |
| Subjects: | Supply chains, Integrated software, Problem solving, Sensitivity analysis, Suppliers |
| Abstract: | A product family consists of multiple components, often supplied by various suppliers. It is crucial to consider the supply risk of these suppliers during product family configuration to ensure that orders can be replenished by alternative suppliers in the event of component disruptions. This study establishes a new optimisation model that concurrently addresses product family configuration and supply chain resilience for the first time. The model is further linearised, making it readily solvable using commercial optimisation software packages for smaller-scale problems. A nested genetic algorithm for solving the large-scale problems is also developed. The proposed method is demonstrated through a case study involving e-book products. The numerical results indicate that the joint optimisation method outperforms other methods, and the nested genetic algorithm achieves high-quality near-optimal solutions with good stability. A sensitivity analysis based on the e-book case assesses the impact of several parameters on profit, including supplier flexibility, unit loss cost, and disruption probability. The findings underscore the importance of supplier flexibility in supplier selection and suggest that companies should carefully evaluate unit loss costs across different module instances, as well as the regional risks associated with suppliers. [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: 185784440 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Joint optimisation of product family configuration and supply chain resilience. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zeng%2C+Ming%22">Zeng, Ming</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ye%2C+Yangyang%22">Ye, Yangyang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Luo%2C+Xinggang%22">Luo, Xinggang</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> xgluo@mail.neu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Chen%2C+Wenchong%22">Chen, Wenchong</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Zhongliang%22">Zhang, Zhongliang</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zeng%2C+Ruochen%22">Zeng, Ruochen</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> rczeng@shu.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>. Jun2025, Vol. 63 Issue 11, p4163-4179. 17p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Supply+chains%22">Supply chains</searchLink><br /><searchLink fieldCode="DE" term="%22Integrated+software%22">Integrated software</searchLink><br /><searchLink fieldCode="DE" term="%22Problem+solving%22">Problem solving</searchLink><br /><searchLink fieldCode="DE" term="%22Sensitivity+analysis%22">Sensitivity analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Suppliers%22">Suppliers</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: A product family consists of multiple components, often supplied by various suppliers. It is crucial to consider the supply risk of these suppliers during product family configuration to ensure that orders can be replenished by alternative suppliers in the event of component disruptions. This study establishes a new optimisation model that concurrently addresses product family configuration and supply chain resilience for the first time. The model is further linearised, making it readily solvable using commercial optimisation software packages for smaller-scale problems. A nested genetic algorithm for solving the large-scale problems is also developed. The proposed method is demonstrated through a case study involving e-book products. The numerical results indicate that the joint optimisation method outperforms other methods, and the nested genetic algorithm achieves high-quality near-optimal solutions with good stability. A sensitivity analysis based on the e-book case assesses the impact of several parameters on profit, including supplier flexibility, unit loss cost, and disruption probability. The findings underscore the importance of supplier flexibility in supplier selection and suggest that companies should carefully evaluate unit loss costs across different module instances, as well as the regional risks associated with suppliers. [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: 10.1080/00207543.2024.2439367 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 4163 Subjects: – SubjectFull: Supply chains Type: general – SubjectFull: Integrated software Type: general – SubjectFull: Problem solving Type: general – SubjectFull: Sensitivity analysis Type: general – SubjectFull: Suppliers Type: general Titles: – TitleFull: Joint optimisation of product family configuration and supply chain resilience. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zeng, Ming – PersonEntity: Name: NameFull: Ye, Yangyang – PersonEntity: Name: NameFull: Luo, Xinggang – PersonEntity: Name: NameFull: Chen, Wenchong – PersonEntity: Name: NameFull: Zhang, Zhongliang – PersonEntity: Name: NameFull: Zeng, Ruochen IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 00207543 Numbering: – Type: volume Value: 63 – Type: issue Value: 11 Titles: – TitleFull: International Journal of Production Research Type: main |
| ResultId | 1 |
