The Multi-Swarm Particle Swarm Optimization Algorithm for Vehicle Routing Problem
Du Taotao, Liu Sheng

Abstract
Aiming at the precocious convergence problem of particle swam optimization, multi-swarm particle swarm optimization algorithm based on particle evolution is presented. The algorithm uses local version of the particle swarm optimization method, from “particle evolution” and “multiple groups” aspects to improve standard particle swarm algorithms. Multiple particle swarm searches solution space independently which keeps diversities of particle populations and improves the stability of the algorithm effectively. The experimental results show that the new algorithm has advantages of convergence property, convergence speed, accuracy and the stability of convergence effective

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