说明：  结合多智能体的学习、协调策略及粒子群算法，提出了一种基于多智能体粒子群优化的配电网络重构方法。该方法采用粒子群算法的拓扑结构来构建多智能体的体系结构，在多智能体系统中，每一个粒子作为一个智能体，通过与邻域的智能体竞争、合作。能够更快、更精确地收敛到全局最优解。粒子的更新规则减少了算法不可行解的产生，提高了算法效率。实验结果表明，该方法具有很高的搜索效率和寻优性能。
(Combining the study of multi-agent technology，coordinating strategies with P$O，a Multi-Agent Particle Swarm Optimization(MA-PSO)algorithm is presented to handle distribution network reconfiguration problem．It applies Von Neuman architecture of Particle Swarm Optimization algorithm to the composition of multi-agent system．An agent in MA-PSO represents a particle to PSO and a candidate solution to the optimization problem．In order to decrease fitness value quickly，agents compete and cooper-ate with their agent of neighboring area．Making use of these agent—agent interactions，MA—PSO realizes the purpose of minimizing the value of objective function．The rules of particle renovating reduce unfeasible solution in the process of particle renovating，which raises the algorithm efficiency satty．The experiment results indicate the prominent efficiency and significant global optima searching performance of MS—PSO．)