New improved hybrid genetic algorithm for optimizing facility layout design of reconfigurable manufacturing system
Abstract The equipment layout design of a reconfigurable manufacturing system can be determined by a variety of algorithms. The complexity of the problem increases with the increase of dimension, and it is a typical NP hard problem. In this paper, a new improved hybrid genetic algorithm is proposed...
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-97526-x |
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| author | Xiaoxiao Wei Jiafan Sun Haojin Jiao |
| author_facet | Xiaoxiao Wei Jiafan Sun Haojin Jiao |
| author_sort | Xiaoxiao Wei |
| collection | DOAJ |
| description | Abstract The equipment layout design of a reconfigurable manufacturing system can be determined by a variety of algorithms. The complexity of the problem increases with the increase of dimension, and it is a typical NP hard problem. In this paper, a new improved hybrid genetic algorithm is proposed to solve this problem. Firstly, the chaos genetic algorithm based on improved Tent map is used to enhance the quality and diversity of the initial population. In order to reduce the complexity of the problem, this paper applies the association rule theory to mine the dominant blocks in the population and to combine the artificial chromosomes. After matched crossover and mutation operations on the layout encoding string, a small adaptive chaotic perturbation is applied to the genetically optimized optimal solution. Finally, through comparison of experimental results and algorithms, it can be concluded that the proposed method is superior to traditional methods in terms of both accuracy and efficiency. |
| format | Article |
| id | doaj-art-5bb9bb37b3dd4a52ab356c0c4e6bb31b |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-5bb9bb37b3dd4a52ab356c0c4e6bb31b2025-08-20T03:03:42ZengNature PortfolioScientific Reports2045-23222025-07-0115111510.1038/s41598-025-97526-xNew improved hybrid genetic algorithm for optimizing facility layout design of reconfigurable manufacturing systemXiaoxiao Wei0Jiafan Sun1Haojin Jiao2School of Modern Post, Xi ’an University of Posts and TelecommunicationsSchool of Modern Post, Xi ’an University of Posts and TelecommunicationsSchool of Modern Post, Xi ’an University of Posts and TelecommunicationsAbstract The equipment layout design of a reconfigurable manufacturing system can be determined by a variety of algorithms. The complexity of the problem increases with the increase of dimension, and it is a typical NP hard problem. In this paper, a new improved hybrid genetic algorithm is proposed to solve this problem. Firstly, the chaos genetic algorithm based on improved Tent map is used to enhance the quality and diversity of the initial population. In order to reduce the complexity of the problem, this paper applies the association rule theory to mine the dominant blocks in the population and to combine the artificial chromosomes. After matched crossover and mutation operations on the layout encoding string, a small adaptive chaotic perturbation is applied to the genetically optimized optimal solution. Finally, through comparison of experimental results and algorithms, it can be concluded that the proposed method is superior to traditional methods in terms of both accuracy and efficiency.https://doi.org/10.1038/s41598-025-97526-xReconfigurable manufacturing systemGenetic algorithmChaos algorithmAssociation rulesDominant block |
| spellingShingle | Xiaoxiao Wei Jiafan Sun Haojin Jiao New improved hybrid genetic algorithm for optimizing facility layout design of reconfigurable manufacturing system Scientific Reports Reconfigurable manufacturing system Genetic algorithm Chaos algorithm Association rules Dominant block |
| title | New improved hybrid genetic algorithm for optimizing facility layout design of reconfigurable manufacturing system |
| title_full | New improved hybrid genetic algorithm for optimizing facility layout design of reconfigurable manufacturing system |
| title_fullStr | New improved hybrid genetic algorithm for optimizing facility layout design of reconfigurable manufacturing system |
| title_full_unstemmed | New improved hybrid genetic algorithm for optimizing facility layout design of reconfigurable manufacturing system |
| title_short | New improved hybrid genetic algorithm for optimizing facility layout design of reconfigurable manufacturing system |
| title_sort | new improved hybrid genetic algorithm for optimizing facility layout design of reconfigurable manufacturing system |
| topic | Reconfigurable manufacturing system Genetic algorithm Chaos algorithm Association rules Dominant block |
| url | https://doi.org/10.1038/s41598-025-97526-x |
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