Xu Xizhen, Wang Qun, Ding Xiaoxin, Chen Tiebing, Deng Ronghui
School of Construction Engineering, Shenzhen Polytechnic University, Shenzhen, 518055, China.
School of Economics and Management, Beijing Jiaotong University, Beijing, 100044, China.
Sci Rep. 2025 Aug 28;15(1):31683. doi: 10.1038/s41598-025-17216-6.
A multi-objective optimization design approach for prefabricated components such as columns, beams, slabs, walls and stairs in prefabricated buildings using ant colony algorithm is proposed to minimize cost, duration and carbon emissions in this paper. The proposed approach takes cost, duration, and carbon emissions as objective functions, the construction technologies of cast-in-place and prefabricated components as variables, prefabrication rate as constraints, and the ant colony algorithm as a solution tool, to minimize the cost, duration, and carbon emissions of prefabricated buildings. The validity of the proposed approach was verified by applying it to the multi-objective optimization design of a three-story frame structure. The results showed that:(1) Compared to all cast-in-place buildings, the prefabricated building under the baseline scenario achieves a reduction of 0.42% in cost, 19.05% in duration, and 13.49% in carbon emissions. (2) The main factor influencing the optimal combination of prefabricated building components is the incremental benefit of cost, duration, and carbon emissions resulting from changes in sub-target weight and prefabrication rate. The weight coefficients of each sub-objective determine "how" the construction technologies of the components is selected, while the prefabrication rate determines "how much" of the construction technologies is chosen. (3) Under four scenarios with different weighting coefficients, the optimized solution for prefabricated buildings compared to cast-in-place construction shows maximum reductions of 1.26% in cost, 27.89% in duration, and 18.4% in carbon emissions. The proposed approach provides an effective pathway for the transformation from cast-in-place construction to prefabricated construction and promotes sustainable development in the building industry.
本文提出一种基于蚁群算法的装配式建筑柱、梁、板、墙、楼梯等预制构件多目标优化设计方法，以实现成本、工期和碳排放的最小化。该方法以成本、工期和碳排放为目标函数，现浇构件和预制构件的施工技术为变量，预制率为约束条件，蚁群算法为求解工具，以实现装配式建筑成本、工期和碳排放的最小化。将该方法应用于某三层框架结构的多目标优化设计，验证了其有效性。结果表明：（1）与全现浇建筑相比，基准方案下的装配式建筑成本降低0.42%，工期缩短19.05%，碳排放减少13.49%。（2）影响装配式建筑构件最优组合的主要因素是子目标权重和预制率变化所带来的成本、工期和碳排放的增量效益。各子目标的权重系数决定了构件施工技术的“如何”选择，而预制率则决定了施工技术的“多少”选择。（3）在四种不同权重系数的方案下，装配式建筑与现浇建筑相比的优化方案成本最大降低1.26%，工期最大缩短27.89%，碳排放最大减少18.4%。该方法为从现浇施工向预制施工的转变提供了有效途径，促进了建筑行业的可持续发展。
