Multi-objective Optimization of Construction Project Based on Improved Ant Colony Algorithm
It is the key and difficult problem for the current project management to consider the multi-objective optimization of the four elements, such as quality, duration, cost and safety. To improve the accuracy and efficiency of project management during the engineering construction, considering the adva...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2020-01-01
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| Series: | Tehnički Vjesnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/340515 |
| _version_ | 1797207287747575808 |
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| author | Yancang Li Shuren Wang* Yongsheng He |
| author_facet | Yancang Li Shuren Wang* Yongsheng He |
| author_sort | Yancang Li |
| collection | DOAJ |
| description | It is the key and difficult problem for the current project management to consider the multi-objective optimization of the four elements, such as quality, duration, cost and safety. To improve the accuracy and efficiency of project management during the engineering construction, considering the advantages and disadvantages of the traditional quality-cost-time model, the four elements were regarded as a system, and a multi-objective optimization model was established. The improved ant colony algorithm was used to carry out multi-objectives of construction projects to overcome the premature defect of the traditional method. The optimal plan of the project was found and the overall efficiency of the construction project management was improved. Results show the optimized ant colony algorithm can avoid the low efficiency of the optimal solution search and the shortcoming of the initial pheromone. The engineering practice proves that the enhanced algorithm has solved the problem of the multi-objective optimization of quality, duration, cost and safety. The obtained conclusions are of significant reference value to direct the similar engineering practice. |
| first_indexed | 2024-04-24T09:20:31Z |
| format | Article |
| id | doaj.art-96b4eb3fe95441fd9af03c8ae2ee59cc |
| institution | Directory Open Access Journal |
| issn | 1330-3651 1848-6339 |
| language | English |
| last_indexed | 2024-04-24T09:20:31Z |
| publishDate | 2020-01-01 |
| publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
| record_format | Article |
| series | Tehnički Vjesnik |
| spelling | doaj.art-96b4eb3fe95441fd9af03c8ae2ee59cc2024-04-15T16:04:15ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392020-01-0127118419010.17559/TV-20191212113720Multi-objective Optimization of Construction Project Based on Improved Ant Colony AlgorithmYancang Li0Shuren Wang*1Yongsheng He2School of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, No. 19, Taiji Road, Handan, Hebei Province, 056038, ChinaInternational Joint Research Laboratory of Henan Province for Underground Space Development and Disaster Prevention, Henan Polytechnic University, No. 2001 Century Avenue, Jiaozuo, Henan Province, 454003, ChinaInstitute of National Defence Engineering, Academy of Military Sciences, No. 3 Xishan Road, Luoyang, Henan Province, 471023, ChinaIt is the key and difficult problem for the current project management to consider the multi-objective optimization of the four elements, such as quality, duration, cost and safety. To improve the accuracy and efficiency of project management during the engineering construction, considering the advantages and disadvantages of the traditional quality-cost-time model, the four elements were regarded as a system, and a multi-objective optimization model was established. The improved ant colony algorithm was used to carry out multi-objectives of construction projects to overcome the premature defect of the traditional method. The optimal plan of the project was found and the overall efficiency of the construction project management was improved. Results show the optimized ant colony algorithm can avoid the low efficiency of the optimal solution search and the shortcoming of the initial pheromone. The engineering practice proves that the enhanced algorithm has solved the problem of the multi-objective optimization of quality, duration, cost and safety. The obtained conclusions are of significant reference value to direct the similar engineering practice.https://hrcak.srce.hr/file/340515ant colony algorithmfitness functionmodelmulti-objective optimizationproject management |
| spellingShingle | Yancang Li Shuren Wang* Yongsheng He Multi-objective Optimization of Construction Project Based on Improved Ant Colony Algorithm Tehnički Vjesnik ant colony algorithm fitness function model multi-objective optimization project management |
| title | Multi-objective Optimization of Construction Project Based on Improved Ant Colony Algorithm |
| title_full | Multi-objective Optimization of Construction Project Based on Improved Ant Colony Algorithm |
| title_fullStr | Multi-objective Optimization of Construction Project Based on Improved Ant Colony Algorithm |
| title_full_unstemmed | Multi-objective Optimization of Construction Project Based on Improved Ant Colony Algorithm |
| title_short | Multi-objective Optimization of Construction Project Based on Improved Ant Colony Algorithm |
| title_sort | multi objective optimization of construction project based on improved ant colony algorithm |
| topic | ant colony algorithm fitness function model multi-objective optimization project management |
| url | https://hrcak.srce.hr/file/340515 |
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