Abstract: This paper gives a local near neighborhood Particle Swarm Optimization（PSO） algorithm that can optimize the unfeasible particle’s position.By dividing the particle swarm into several overlapping subgroups and looking for near neighbors in various subgroups，the proposed algorithm can effectively improve the learning of particles and increase the speed of particles to find neighbors.It can also increase the speed to search the optimized result via optimizing the unfeasible particles.The experiment results prove the high efficiency of the algorithm to solve the vehicle routing problem with time windows.

摘要： 设计了一种引入局部近邻机制并且能够优化不可行解的粒子群算法。该算法将粒子群分成相互重叠的子群，在各个子群内寻找近邻，提高了粒子的学习功能和寻找近邻的速度；同时将产生的不可行解进行局部优化，增强了粒子寻找最优的能力。实验结果表明：该算法可以快速求得带时间窗车辆路径问题的满意解。