A neo-cooperation search based evolutionary algorithm for multi-objective electric rope shovel production scheduling
In the manufacturing process of electric rope shovels, an extensive array of components need to be processed. Each component is subject to a distinct sequence of operations, with the number of operations varying by part. Moreover, each of these operations needs to be processed on specific machines w...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-04-01
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| Series: | Frontiers in Mechanical Engineering |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmech.2025.1529235/full |
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| author | Jue Zhang Haifeng Yue Yongpeng Wang Ruhan Guo Shuai Shao |
| author_facet | Jue Zhang Haifeng Yue Yongpeng Wang Ruhan Guo Shuai Shao |
| author_sort | Jue Zhang |
| collection | DOAJ |
| description | In the manufacturing process of electric rope shovels, an extensive array of components need to be processed. Each component is subject to a distinct sequence of operations, with the number of operations varying by part. Moreover, each of these operations needs to be processed on specific machines within specific processing durations. Therefore, the electric rope shovel production scheduling problem turns out to be challenging for general optimizers, requiring to find the optimal operation sequence, make trade-offs between multiple conflicting objectives, and satisfy a series of strict constraints. To address this production scheduling problem, this paper proposes a neo-cooperation search based evolutionary algorithm. The proposed algorithm suggests a novel encoding scheme to represent a solution (i.e., the sequence of operations of multiple components) with a real decision vector and allocates computational resources to two cooperating populations for global search and local search, respectively. The proposed algorithm can effectively balance between exploration and exploitation, and is shown to outperform state-of-the-art evolutionary algorithms in the experiments. |
| format | Article |
| id | doaj-art-441730dc571e4cc8ac4e34f209c316f2 |
| institution | OA Journals |
| issn | 2297-3079 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Mechanical Engineering |
| spelling | doaj-art-441730dc571e4cc8ac4e34f209c316f22025-08-20T02:26:24ZengFrontiers Media S.A.Frontiers in Mechanical Engineering2297-30792025-04-011110.3389/fmech.2025.15292351529235A neo-cooperation search based evolutionary algorithm for multi-objective electric rope shovel production schedulingJue Zhang0Haifeng Yue1Yongpeng Wang2Ruhan Guo3Shuai Shao4State Key Laboratory of Intelligent Mining Equipment Technology, Taiyuan, ChinaState Key Laboratory of Intelligent Mining Equipment Technology, Taiyuan, ChinaState Key Laboratory of Intelligent Mining Equipment Technology, Taiyuan, ChinaState Key Laboratory of Intelligent Mining Equipment Technology, Taiyuan, ChinaSchool of Computer Science and Technology, Anhui University, Hefei, ChinaIn the manufacturing process of electric rope shovels, an extensive array of components need to be processed. Each component is subject to a distinct sequence of operations, with the number of operations varying by part. Moreover, each of these operations needs to be processed on specific machines within specific processing durations. Therefore, the electric rope shovel production scheduling problem turns out to be challenging for general optimizers, requiring to find the optimal operation sequence, make trade-offs between multiple conflicting objectives, and satisfy a series of strict constraints. To address this production scheduling problem, this paper proposes a neo-cooperation search based evolutionary algorithm. The proposed algorithm suggests a novel encoding scheme to represent a solution (i.e., the sequence of operations of multiple components) with a real decision vector and allocates computational resources to two cooperating populations for global search and local search, respectively. The proposed algorithm can effectively balance between exploration and exploitation, and is shown to outperform state-of-the-art evolutionary algorithms in the experiments.https://www.frontiersin.org/articles/10.3389/fmech.2025.1529235/fullevolutionary computationconstrained optimizationsequence optimizationco-evolutionary algorithmsmulti-obj ective optimization problems |
| spellingShingle | Jue Zhang Haifeng Yue Yongpeng Wang Ruhan Guo Shuai Shao A neo-cooperation search based evolutionary algorithm for multi-objective electric rope shovel production scheduling Frontiers in Mechanical Engineering evolutionary computation constrained optimization sequence optimization co-evolutionary algorithms multi-obj ective optimization problems |
| title | A neo-cooperation search based evolutionary algorithm for multi-objective electric rope shovel production scheduling |
| title_full | A neo-cooperation search based evolutionary algorithm for multi-objective electric rope shovel production scheduling |
| title_fullStr | A neo-cooperation search based evolutionary algorithm for multi-objective electric rope shovel production scheduling |
| title_full_unstemmed | A neo-cooperation search based evolutionary algorithm for multi-objective electric rope shovel production scheduling |
| title_short | A neo-cooperation search based evolutionary algorithm for multi-objective electric rope shovel production scheduling |
| title_sort | neo cooperation search based evolutionary algorithm for multi objective electric rope shovel production scheduling |
| topic | evolutionary computation constrained optimization sequence optimization co-evolutionary algorithms multi-obj ective optimization problems |
| url | https://www.frontiersin.org/articles/10.3389/fmech.2025.1529235/full |
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