Improved Self-Learning Genetic Algorithm for Solving Flexible Job Shop Scheduling
The flexible job shop scheduling problem (FJSP), one of the core problems in the field of generative manufacturing process planning, has become a hotspot and a challenge in manufacturing production research. In this study, an improved self-learning genetic algorithm is proposed. The single mutation...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/11/22/4700 |
| _version_ | 1827639365898076160 |
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| author | Ming Jiang Haihan Yu Jiaqing Chen |
| author_facet | Ming Jiang Haihan Yu Jiaqing Chen |
| author_sort | Ming Jiang |
| collection | DOAJ |
| description | The flexible job shop scheduling problem (FJSP), one of the core problems in the field of generative manufacturing process planning, has become a hotspot and a challenge in manufacturing production research. In this study, an improved self-learning genetic algorithm is proposed. The single mutation approach of the genetic algorithm was improved, while four mutation operators were designed on the basis of process coding and machine coding; their weights were updated and their selection mutation operators were adjusted according to the performance in the iterative process. Combined with the improved population initialization method and the optimized crossover strategy, the local search capability was enhanced, and the convergence speed was accelerated. The effectiveness and feasibility of the algorithm were verified by testing the benchmark arithmetic examples and numerical experiments. |
| first_indexed | 2024-03-09T16:38:28Z |
| format | Article |
| id | doaj.art-b3f6850a2a1f4614b501927d051962f0 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-09T16:38:28Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-b3f6850a2a1f4614b501927d051962f02023-11-24T14:54:32ZengMDPI AGMathematics2227-73902023-11-011122470010.3390/math11224700Improved Self-Learning Genetic Algorithm for Solving Flexible Job Shop SchedulingMing Jiang0Haihan Yu1Jiaqing Chen2School of Internet Economics and Business, Fujian University of Technology, Fuzhou 350014, ChinaSchool of Internet Economics and Business, Fujian University of Technology, Fuzhou 350014, ChinaSchool of Economics and Finance, Xi’an Jiaotong University, Xi’an 710061, ChinaThe flexible job shop scheduling problem (FJSP), one of the core problems in the field of generative manufacturing process planning, has become a hotspot and a challenge in manufacturing production research. In this study, an improved self-learning genetic algorithm is proposed. The single mutation approach of the genetic algorithm was improved, while four mutation operators were designed on the basis of process coding and machine coding; their weights were updated and their selection mutation operators were adjusted according to the performance in the iterative process. Combined with the improved population initialization method and the optimized crossover strategy, the local search capability was enhanced, and the convergence speed was accelerated. The effectiveness and feasibility of the algorithm were verified by testing the benchmark arithmetic examples and numerical experiments.https://www.mdpi.com/2227-7390/11/22/4700self-learning genetic algorithmflexible job shop schedulingself-learning variational strategy |
| spellingShingle | Ming Jiang Haihan Yu Jiaqing Chen Improved Self-Learning Genetic Algorithm for Solving Flexible Job Shop Scheduling Mathematics self-learning genetic algorithm flexible job shop scheduling self-learning variational strategy |
| title | Improved Self-Learning Genetic Algorithm for Solving Flexible Job Shop Scheduling |
| title_full | Improved Self-Learning Genetic Algorithm for Solving Flexible Job Shop Scheduling |
| title_fullStr | Improved Self-Learning Genetic Algorithm for Solving Flexible Job Shop Scheduling |
| title_full_unstemmed | Improved Self-Learning Genetic Algorithm for Solving Flexible Job Shop Scheduling |
| title_short | Improved Self-Learning Genetic Algorithm for Solving Flexible Job Shop Scheduling |
| title_sort | improved self learning genetic algorithm for solving flexible job shop scheduling |
| topic | self-learning genetic algorithm flexible job shop scheduling self-learning variational strategy |
| url | https://www.mdpi.com/2227-7390/11/22/4700 |
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