Multi-objective optimization of construction based on genetic algorithm NSGA-II

Multi-objective optimization, as an important method in architectural design, directly affects the operational efficiency of energy systems by controlling the quality and implementation effectiveness of instructions. To raise the efficiency, quality, and financial savings of building, a multi-objective optimization model grounded on schedule, cost, and quality was studied and designed. During the process, a span model, a span cost model, and a span quality model were established separately. Finally, a multi-objective optimization model for project duration, spend, and quality was established, and an evaluation function for the model was developed based on the Euclidean distance short ideal point method. Genetic algorithm was utilized to manage the model. The experiment outcomes showed that there were 152 working days for a construction period of 320 days, while after optimization, it was only 90 days. The original plan had a span of 350 days and a spend of 3.8 million yuan, respectively. Optimization Plan 1 optimized the duration and cost targets of the original plan by 9.38% and 11.76%, respectively, with good optimization results. The research methodology seamlessly incorporates various objectives, including project duration, cost, and quality, proving both feasible and efficient. This approach enhances application effectiveness and elevates the management standards within the realm of project management. Research can provide certain technical references for construction project management.

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Publication Details

Journal
International Journal of Architectural Computing
Published
2025-04-15
DOI
https://doi.org/10.1177/14780771251335107
Citations
1
Primary Topic
BIM and Construction Integration
Type
article
Field-Weighted Citation Impact
1.01
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article

Multi-objective optimization of construction based on genetic algorithm NSGA-II

Yingying Zhang, Renjie Wang
1 citations
International Journal of Architectural Computing
BIM and Construction Integration
1.01
article

Multi-objective optimization of construction based on genetic algorithm NSGA-II

Yingying Zhang, Renjie Wang
article en
1 citations

Abstract

Multi-objective optimization, as an important method in architectural design, directly affects the operational efficiency of energy systems by controlling the quality and implementation effectiveness of instructions. To raise the efficiency, quality, and financial savings of building, a multi-objective optimization model grounded on schedule, cost, and quality was studied and designed. During the process, a span model, a span cost model, and a span quality model were established separately. Finally, a multi-objective optimization model for project duration, spend, and quality was established, and an evaluation function for the model was developed based on the Euclidean distance short ideal point method. Genetic algorithm was utilized to manage the model. The experiment outcomes showed that there were 152 working days for a construction period of 320 days, while after optimization, it was only 90 days. The original plan had a span of 350 days and a spend of 3.8 million yuan, respectively. Optimization Plan 1 optimized the duration and cost targets of the original plan by 9.38% and 11.76%, respectively, with good optimization results. The research methodology seamlessly incorporates various objectives, including project duration, cost, and quality, proving both feasible and efficient. This approach enhances application effectiveness and elevates the management standards within the realm of project management. Research can provide certain technical references for construction project management.

International Journal of Architectural Computing
Kaifeng University (CN), Dongfeng Motor Group (China) (CN)
Openalex Percentile: Top 26%
BIM and Construction Integration
1.01
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