Improved Chaos Particle swarm Algorithm on VRP

Convergence speed,accuracy and the ability of global search is very important for intelligent algorithms that can be improved by any way.Due to the existing PSO search algorithm is liable to cause some problems in the later,such as the precocity,local optimum and slow convergence speed.An improved algorithm is proposed in this paper,it can improve the local search ability of particle swarm.On the basis of particle swarm optimization(PSO)algorithm,chaotic PSO algorithm is improved.Specifically,it presents to get the average optimal solution for the position of each iteration instead of individual optimal solution and to do chaos optimization for the optimal position after processing.At the same time,it adds the shrinkage factor to improve the convergence speed to ensure balance and global convergence of the algorithm.The simulation results about vehicle routing problems show that the improved algorithm is better than that of refs,especially in optimization accuracy and global convergence ability.And it is also an effective method to solve the VRP problem.