Research on Assembly Sequence Planning of Large Cruise Ship Cabins Based on Improved Genetic Algorithm
In the construction process of large cruise ships, there are numerous cabin components, and the number of assembly sequences will experience a “combinatorial explosion”, which will become a complex NP hard problem. This article proposes an assembly sequence planning method based on practical enginee...
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MDPI AG
2025-04-01
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| Series: | Biomimetics |
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| Online Access: | https://www.mdpi.com/2313-7673/10/4/237 |
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| author | Liyang Ju Xiaoyuan Wu Yixi Zhao Jianfeng Liu Kun Liu |
| author_facet | Liyang Ju Xiaoyuan Wu Yixi Zhao Jianfeng Liu Kun Liu |
| author_sort | Liyang Ju |
| collection | DOAJ |
| description | In the construction process of large cruise ships, there are numerous cabin components, and the number of assembly sequences will experience a “combinatorial explosion”, which will become a complex NP hard problem. This article proposes an assembly sequence planning method based on practical engineering problems in the construction process of large cruise ships. The cabin components are modularized, and an optimization algorithm is designed for multi-objective problem solving to obtain the optimal assembly sequence of cabin components. This article analyzes the impact of six constraint conditions on the assembly plan, including geometric constraints, sequence constraints, number of assembly reversals, number of tool replacements, stable connection relationships, and selection of reference components. A fitness function is designed and a mathematical model is established. On this basis, a genetic greedy combination algorithm is proposed to solve the optimal assembly sequence. Compared with traditional genetic algorithms, this improves computational efficiency and solves complex problems in a better manner. Multiple unique optimal solutions can be obtained in one solution process. The feasibility and effectiveness of this method were verified through examples. |
| format | Article |
| id | doaj-art-4d96f885496b41ee8da38d3f75b84449 |
| institution | OA Journals |
| issn | 2313-7673 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomimetics |
| spelling | doaj-art-4d96f885496b41ee8da38d3f75b844492025-08-20T02:17:25ZengMDPI AGBiomimetics2313-76732025-04-0110423710.3390/biomimetics10040237Research on Assembly Sequence Planning of Large Cruise Ship Cabins Based on Improved Genetic AlgorithmLiyang Ju0Xiaoyuan Wu1Yixi Zhao2Jianfeng Liu3Kun Liu4School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 201109, ChinaShanghai Waigaoqiao Shipbuilding Co., Ltd., Shanghai 200137, ChinaSchool of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 201109, ChinaShanghai Waigaoqiao Shipbuilding Co., Ltd., Shanghai 200137, ChinaSchool of Naval Architecture and Ocean Engineering, Jiangsu University of Science and Technology, Zhenjiang 212100, ChinaIn the construction process of large cruise ships, there are numerous cabin components, and the number of assembly sequences will experience a “combinatorial explosion”, which will become a complex NP hard problem. This article proposes an assembly sequence planning method based on practical engineering problems in the construction process of large cruise ships. The cabin components are modularized, and an optimization algorithm is designed for multi-objective problem solving to obtain the optimal assembly sequence of cabin components. This article analyzes the impact of six constraint conditions on the assembly plan, including geometric constraints, sequence constraints, number of assembly reversals, number of tool replacements, stable connection relationships, and selection of reference components. A fitness function is designed and a mathematical model is established. On this basis, a genetic greedy combination algorithm is proposed to solve the optimal assembly sequence. Compared with traditional genetic algorithms, this improves computational efficiency and solves complex problems in a better manner. Multiple unique optimal solutions can be obtained in one solution process. The feasibility and effectiveness of this method were verified through examples.https://www.mdpi.com/2313-7673/10/4/237large cruise ship cabinsassembly sequence planninggenetic greedy combination algorithmmulti-objective optimization |
| spellingShingle | Liyang Ju Xiaoyuan Wu Yixi Zhao Jianfeng Liu Kun Liu Research on Assembly Sequence Planning of Large Cruise Ship Cabins Based on Improved Genetic Algorithm Biomimetics large cruise ship cabins assembly sequence planning genetic greedy combination algorithm multi-objective optimization |
| title | Research on Assembly Sequence Planning of Large Cruise Ship Cabins Based on Improved Genetic Algorithm |
| title_full | Research on Assembly Sequence Planning of Large Cruise Ship Cabins Based on Improved Genetic Algorithm |
| title_fullStr | Research on Assembly Sequence Planning of Large Cruise Ship Cabins Based on Improved Genetic Algorithm |
| title_full_unstemmed | Research on Assembly Sequence Planning of Large Cruise Ship Cabins Based on Improved Genetic Algorithm |
| title_short | Research on Assembly Sequence Planning of Large Cruise Ship Cabins Based on Improved Genetic Algorithm |
| title_sort | research on assembly sequence planning of large cruise ship cabins based on improved genetic algorithm |
| topic | large cruise ship cabins assembly sequence planning genetic greedy combination algorithm multi-objective optimization |
| url | https://www.mdpi.com/2313-7673/10/4/237 |
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