针对建设项目的复杂性和动态性,建立基于改进微粒群算法的多目标动态优化模型.首先,为提高算法性能,引入外部归档集和阈值并构建基于理想点法的适应度函数;其次,分别建立工期模型、加入系统可靠度的质量模型以及加入费用现值的成本模型,由其得到综合优化模型;最后结合工程实例对算法进行验证并与非劣分类遗传算法(NSGA-Ⅱ算法)对比.结果表明:方法比NSGA-Ⅱ算法的优化结果更科学、收敛速度更快. According to the complexity and dynamic of construction project, a multi-objective dynamic optimization model based on improved particle swarm optimization is established.Firstly, in order to improve the performance of the algorithm, the external archive set and threshold are introduced and the fitness function based on the ideal point method is constructed. Secondly, Establish the model of the duration, add the quality model of the system reliability and the cost model of adding the present value of the cost, and obtain the comprehensive optimization model; Finally, the algorithm is verified with the engineering example and compared with the non-inferior classification genetic algorithm (NSGA-Ⅱ). The results show that the method is more scientific than NSGA-Ⅱ, and the convergence speed is faster.