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．