Multi-objective optimization analysis of construction management site layout based on improved genetic algorithm
In construction management, the rationality of on-site layout is crucial for project progress, cost, and safety. In order to improve the rationality of on-site layout, a multi-objective optimization model combining ant colony algorithm and Pareto optimal solution was constructed based on genetic alg...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Systems and Soft Computing |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772941924000425 |
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| author | Hui Yin |
| author_facet | Hui Yin |
| author_sort | Hui Yin |
| collection | DOAJ |
| description | In construction management, the rationality of on-site layout is crucial for project progress, cost, and safety. In order to improve the rationality of on-site layout, a multi-objective optimization model combining ant colony algorithm and Pareto optimal solution was constructed based on genetic algorithm, and this model was applied to practical engineering cases. The results show that in terms of computational time, the genetic algorithm takes an average of 1702.0 s, while the improved algorithm takes an average of 421.0 s, which is 1281s less and 85.9% more than before the improvement. The performance of the improved algorithm is the best, and the optimal solution can be obtained through multiple iterations. The improved algorithm has improved the efficiency of on-site layout optimization, and possesses practical application value for the layout of construction management sites. It offers a certain reference for the reasonable setting of construction management sites. |
| format | Article |
| id | doaj-art-e5691235d58f4241be951ce199aaa29c |
| institution | OA Journals |
| issn | 2772-9419 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Systems and Soft Computing |
| spelling | doaj-art-e5691235d58f4241be951ce199aaa29c2025-08-20T01:58:30ZengElsevierSystems and Soft Computing2772-94192024-12-01620011310.1016/j.sasc.2024.200113Multi-objective optimization analysis of construction management site layout based on improved genetic algorithmHui Yin0School of Civil Engineering, Xinjiang Institute of Engineering, Urumqi, 830000, ChinaIn construction management, the rationality of on-site layout is crucial for project progress, cost, and safety. In order to improve the rationality of on-site layout, a multi-objective optimization model combining ant colony algorithm and Pareto optimal solution was constructed based on genetic algorithm, and this model was applied to practical engineering cases. The results show that in terms of computational time, the genetic algorithm takes an average of 1702.0 s, while the improved algorithm takes an average of 421.0 s, which is 1281s less and 85.9% more than before the improvement. The performance of the improved algorithm is the best, and the optimal solution can be obtained through multiple iterations. The improved algorithm has improved the efficiency of on-site layout optimization, and possesses practical application value for the layout of construction management sites. It offers a certain reference for the reasonable setting of construction management sites.http://www.sciencedirect.com/science/article/pii/S2772941924000425Construction managementSite layoutMulti objective optimizationGenetic algorithmAnt colony |
| spellingShingle | Hui Yin Multi-objective optimization analysis of construction management site layout based on improved genetic algorithm Systems and Soft Computing Construction management Site layout Multi objective optimization Genetic algorithm Ant colony |
| title | Multi-objective optimization analysis of construction management site layout based on improved genetic algorithm |
| title_full | Multi-objective optimization analysis of construction management site layout based on improved genetic algorithm |
| title_fullStr | Multi-objective optimization analysis of construction management site layout based on improved genetic algorithm |
| title_full_unstemmed | Multi-objective optimization analysis of construction management site layout based on improved genetic algorithm |
| title_short | Multi-objective optimization analysis of construction management site layout based on improved genetic algorithm |
| title_sort | multi objective optimization analysis of construction management site layout based on improved genetic algorithm |
| topic | Construction management Site layout Multi objective optimization Genetic algorithm Ant colony |
| url | http://www.sciencedirect.com/science/article/pii/S2772941924000425 |
| work_keys_str_mv | AT huiyin multiobjectiveoptimizationanalysisofconstructionmanagementsitelayoutbasedonimprovedgeneticalgorithm |