Balancing optimality and efficiency in solving flexible process planning: A parameter-free two-stage algorithm.
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| Title: | Balancing optimality and efficiency in solving flexible process planning: A parameter-free two-stage algorithm. |
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| Authors: | Ma, Yiming1 (AUTHOR), Luo, Kaiping1,2 (AUTHOR) kaipingluo@buaa.edu.cn, Chou, Mabel C.3,4,5 (AUTHOR), Sun, Jianfei6 (AUTHOR) |
| Source: | International Journal of Production Research. Sep2025, Vol. 63 Issue 18, p6877-6894. 18p. |
| Subjects: | Production planning, Metaheuristic algorithms, Algorithms, Process optimization, Manufacturing resource planning, Computer performance |
| Abstract: | Flexible process planning (FPP) involves developing production plans that translate design specifications into manufacturable steps while satisfying technical constraints. Existing FPP methods struggle to provide effective solutions due to the complexities arising from processing, sequencing, and operation flexibility. This paper addresses these challenges by decomposing the FPP problem into three subproblems based on the types of flexibility and proposing a parameter-free two-stage algorithm. In the first stage, a metaheuristic–variable neighbourhood search–is improved to tackle the NP-hard operation sequencing problem. In the second stage, the alternative operation selection and manufacturing resource allocation problems are transformed into a shortest path problem, which can be optimally solved in polynomial time. This two-stage algorithm effectively balances optimality and efficiency. Comparative experiments with six state-of-the-art methods on real-world and large-scale cases demonstrate that the proposed algorithm ranks first in 84.7% of overall performance metrics. Additionally, integrating the second-stage algorithm into existing metaheuristics results in an average performance improvement of 80.4%. These findings highlight the robustness, scalability, and effectiveness of the proposed algorithm, making it highly practical for real-world process planning. [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: 187749451 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Balancing optimality and efficiency in solving flexible process planning: A parameter-free two-stage algorithm. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ma%2C+Yiming%22">Ma, Yiming</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Luo%2C+Kaiping%22">Luo, Kaiping</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> kaipingluo@buaa.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Chou%2C+Mabel+C%2E%22">Chou, Mabel C.</searchLink><relatesTo>3,4,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sun%2C+Jianfei%22">Sun, Jianfei</searchLink><relatesTo>6</relatesTo> (AUTHOR) – 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, p6877-6894. 18p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Production+planning%22">Production planning</searchLink><br /><searchLink fieldCode="DE" term="%22Metaheuristic+algorithms%22">Metaheuristic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Process+optimization%22">Process optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Manufacturing+resource+planning%22">Manufacturing resource planning</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+performance%22">Computer performance</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Flexible process planning (FPP) involves developing production plans that translate design specifications into manufacturable steps while satisfying technical constraints. Existing FPP methods struggle to provide effective solutions due to the complexities arising from processing, sequencing, and operation flexibility. This paper addresses these challenges by decomposing the FPP problem into three subproblems based on the types of flexibility and proposing a parameter-free two-stage algorithm. In the first stage, a metaheuristic–variable neighbourhood search–is improved to tackle the NP-hard operation sequencing problem. In the second stage, the alternative operation selection and manufacturing resource allocation problems are transformed into a shortest path problem, which can be optimally solved in polynomial time. This two-stage algorithm effectively balances optimality and efficiency. Comparative experiments with six state-of-the-art methods on real-world and large-scale cases demonstrate that the proposed algorithm ranks first in 84.7% of overall performance metrics. Additionally, integrating the second-stage algorithm into existing metaheuristics results in an average performance improvement of 80.4%. These findings highlight the robustness, scalability, and effectiveness of the proposed algorithm, making it highly practical for real-world process planning. [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: 10.1080/00207543.2025.2490214 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 6877 Subjects: – SubjectFull: Production planning Type: general – SubjectFull: Metaheuristic algorithms Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Process optimization Type: general – SubjectFull: Manufacturing resource planning Type: general – SubjectFull: Computer performance Type: general Titles: – TitleFull: Balancing optimality and efficiency in solving flexible process planning: A parameter-free two-stage algorithm. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ma, Yiming – PersonEntity: Name: NameFull: Luo, Kaiping – PersonEntity: Name: NameFull: Chou, Mabel C. – PersonEntity: Name: NameFull: Sun, Jianfei 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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