A novel two stage neighborhood search for flexible job shop scheduling problem considering reconfigurable machine tools
Abstract The rapid changes in market demand are driving a transition from traditional mass production to high-mix, low-volume production, emphasizing the need for customization and rapid response. Reconfigurable Manufacturing Systems (RMS) are crucial in this shift, providing a flexible platform to...
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| Format: | Article |
| Language: | English |
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Springer
2025-06-01
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| Series: | Complex & Intelligent Systems |
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| Online Access: | https://doi.org/10.1007/s40747-025-01890-0 |
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| author | Yanjun Shi Chengjia Yu Shiduo Ning |
| author_facet | Yanjun Shi Chengjia Yu Shiduo Ning |
| author_sort | Yanjun Shi |
| collection | DOAJ |
| description | Abstract The rapid changes in market demand are driving a transition from traditional mass production to high-mix, low-volume production, emphasizing the need for customization and rapid response. Reconfigurable Manufacturing Systems (RMS) are crucial in this shift, providing a flexible platform to meet diverse production requirements, and forming an essential component of next-generation manufacturing. Reconfigurable Machine Tools (RMTs), the core of RMS, enable dynamic configuration adjustments through auxiliary modules (AMs), enhancing both flexibility and efficiency. However, optimizing the allocation of limited AMs, considering non-negligible assembly and disassembly times, remains a significant challenge. This paper focuses on the flexible job shop scheduling problem with machine reconfigurations (FJSP-MR) and proposes an improved genetic algorithm with a two-stage neighborhood search (IGA-TNS) to minimize total weighted tardiness (TWT). Initially, a mixed-integer linear programming (MILP) model is formulated to comprehensively represent the problem. To enhance search efficiency, a two-stage neighborhood search strategy is developed: the first stage extends the k-insertion search to facilitate operation movement across different machine configurations, while the second stage refines operations within the same configuration. Furthermore, a trend-detection-based neighborhood search activation strategy is introduced to accelerate convergence and reduce computational costs. Experimental results on extended benchmark instances demonstrate that the proposed IGA-TNS effectively addresses the FJSP-MR, outperforming other algorithms in solution quality and computational efficiency. Finally, a industrial FJSP-MR case is studied, demonstrating that the proposed IGA-TNS is applicable to large-scale problems. |
| format | Article |
| id | doaj-art-91a5f7bdeacb4e328d19b99eace5fdf6 |
| institution | OA Journals |
| issn | 2199-4536 2198-6053 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Springer |
| record_format | Article |
| series | Complex & Intelligent Systems |
| spelling | doaj-art-91a5f7bdeacb4e328d19b99eace5fdf62025-08-20T02:10:32ZengSpringerComplex & Intelligent Systems2199-45362198-60532025-06-0111712310.1007/s40747-025-01890-0A novel two stage neighborhood search for flexible job shop scheduling problem considering reconfigurable machine toolsYanjun Shi0Chengjia Yu1Shiduo Ning2School of Mechanical Engineering, Dalian University of TechnologySchool of Mechanical Engineering, Dalian University of TechnologySchool of Mechanical Engineering, Dalian University of TechnologyAbstract The rapid changes in market demand are driving a transition from traditional mass production to high-mix, low-volume production, emphasizing the need for customization and rapid response. Reconfigurable Manufacturing Systems (RMS) are crucial in this shift, providing a flexible platform to meet diverse production requirements, and forming an essential component of next-generation manufacturing. Reconfigurable Machine Tools (RMTs), the core of RMS, enable dynamic configuration adjustments through auxiliary modules (AMs), enhancing both flexibility and efficiency. However, optimizing the allocation of limited AMs, considering non-negligible assembly and disassembly times, remains a significant challenge. This paper focuses on the flexible job shop scheduling problem with machine reconfigurations (FJSP-MR) and proposes an improved genetic algorithm with a two-stage neighborhood search (IGA-TNS) to minimize total weighted tardiness (TWT). Initially, a mixed-integer linear programming (MILP) model is formulated to comprehensively represent the problem. To enhance search efficiency, a two-stage neighborhood search strategy is developed: the first stage extends the k-insertion search to facilitate operation movement across different machine configurations, while the second stage refines operations within the same configuration. Furthermore, a trend-detection-based neighborhood search activation strategy is introduced to accelerate convergence and reduce computational costs. Experimental results on extended benchmark instances demonstrate that the proposed IGA-TNS effectively addresses the FJSP-MR, outperforming other algorithms in solution quality and computational efficiency. Finally, a industrial FJSP-MR case is studied, demonstrating that the proposed IGA-TNS is applicable to large-scale problems.https://doi.org/10.1007/s40747-025-01890-0Reconfigurable manufacturing systemsFlexible job shop schedulingReconfigurable machine toolsImproved genetic algorithmNeighbourhood search |
| spellingShingle | Yanjun Shi Chengjia Yu Shiduo Ning A novel two stage neighborhood search for flexible job shop scheduling problem considering reconfigurable machine tools Complex & Intelligent Systems Reconfigurable manufacturing systems Flexible job shop scheduling Reconfigurable machine tools Improved genetic algorithm Neighbourhood search |
| title | A novel two stage neighborhood search for flexible job shop scheduling problem considering reconfigurable machine tools |
| title_full | A novel two stage neighborhood search for flexible job shop scheduling problem considering reconfigurable machine tools |
| title_fullStr | A novel two stage neighborhood search for flexible job shop scheduling problem considering reconfigurable machine tools |
| title_full_unstemmed | A novel two stage neighborhood search for flexible job shop scheduling problem considering reconfigurable machine tools |
| title_short | A novel two stage neighborhood search for flexible job shop scheduling problem considering reconfigurable machine tools |
| title_sort | novel two stage neighborhood search for flexible job shop scheduling problem considering reconfigurable machine tools |
| topic | Reconfigurable manufacturing systems Flexible job shop scheduling Reconfigurable machine tools Improved genetic algorithm Neighbourhood search |
| url | https://doi.org/10.1007/s40747-025-01890-0 |
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