An improved algorithm based on Multiagent particle swarm(MAS) is proposed to solve the distribution network reconfiguration problem in this paper.The approach is a combination of the learning, competition and cooperation mechanism of multi-agent technology and the strategies of Particle swarm optimization(PSO) algorithm. Using the Von Neumann topology structure in PSO algorithm, each particle represents an agent; each agent not only competes and cooperates with its neighborhood,but also absorbs the evolutionary mechanism of PSO algorithm, so as to share the information with the agent of global optimal. The rules of particle renovating reduce unfeasible solution in the process of particle renovating,and it is able to converge to global optimal accurately and quickly. Test on the IEEE 16-node, 32-node and 69-node system shows both a rapid convergence and a good robustness of this proposed approach. An improved algorithm based on Multiagent particle swarm (MAS) is proposed to solve the distribution network reconfiguration problem in this paper. The approach is a combination of the learning, competition and cooperation mechanism of multi-agent technology and the strategies of Particle Swarm optimization ( PSO) algorithm. Using the Von Neumann topology structure in PSO algorithm, each particle represents an agent; each agent not only competes and cooperates with its neighborhood, but also absorbs the evolutionary mechanism of PSO algorithm, so as to share the information with the agent of global optimal. The rules of particle renovating reduce unfeasible solution in the process of particle renovating, and it is able to converge to global optimal accurately and quickly. Test on the IEEE 16-node, 32-node and 69-node system shows both a rapid convergence and a good robustness of this proposed approach.