将微粒群算法(particle swarm optimization，PSO)引入工程项目多目标协同优化领域，研究工程项目的质量、费用、资源和工期的协同优化问题。文章首先系统介绍微粒群算法原理、流程以及算法的改进发展，然后研究了工程项目质量、费用、工期和资源的协调功效系数，并建立了质量、费用、工期和资源的多目标协同优化模型，接下来介绍了应用微粒群算法编码解决工程项目多目标优化的方法步骤。最后，通过一个应用实例，计算表明微粒群算法可以准确快速地解决工程项目多目标协同优化问题。

The Particle Swarm Optimization (PSO) is an evolutionary computation, which not only can search solutions randomly and fully, but also is convenient to be carried out. Hence, the article focuses on the application of PSO to the multiple-objective coordination optimization of project, looking forward to seeking best solutions easily and quickly. After introducing the basic theory of the algorithms and its several versions, the article aims at the efficiency coefficient of quality, cost, time and resource subsystem, and set up a multiple optimization coordination model. In the following part, the article introduces how to apply PSO to solve the project coordination optimization problem in detail. The numeric example followed indicates that PSO can solve the multiple-objectives coordination optimization problem of project exactly and quickly.