Optimization of prefabricated building construction based on dragonfly algorithm and BIM technology

• Published in: Journal of computational methods in sciences and engineering
• Main Authors: Min, Hongxia, Xiong, Huan
• Format: Journal Article
• Language: English
• Published: 05.08.2025
• ISSN: 1472-7978; 1875-8983
• DOI: 10.1177/14727978251366535

With the continuous development of construction industrialization, prefabricated buildings have been widely used due to their advantages of resource conservation, shortened construction period, environmental protection, and low pollution. However, the structural optimization design and construction scheduling optimization of prefabricated building concrete components urgently need to be solved to meet the sustainable development. Therefore, the research adopts the dragonfly algorithm optimized by multiple strategies to optimize the overall structure of prefabricated concrete components in buildings. BIM technology is applied to build a construction scheduling optimization model that satisfies resource constraints and structural constraints to optimize the scheduling plan of prefabricated components during assembly construction and find the shortest construction period and optimal scheduling plan. The experimental results show that in the comparison of intelligent algorithm iteration curves, the improved algorithm was superior to the standard DA, Nelder-Mead, NS-FPA, and CPSO algorithms. In the multi-modal function test, the optimal result of the research model was 17.54, while the standard DA, Nelder-Mead, NS-FPA, and LMA algorithms were 72.5, 52.5, and 20.3, respectively. The convergence and optimization performance of the research model were both the best. In the specific construction optimization, the improved algorithm effectively reduced the cost of concrete components and increased the ultimate bearing capacity of welded joints by 6.24%. The construction scheduling optimization model based on BIM technology saved 0.2631 working days, or 6.31 h, improving the work efficiency and reducing cost. This indicates that the research results have application value in the field of prefabricated building optimization.