Improved Chaos Particle swarm Algorithm on VRP
ZHANG Xiaoqing
GONG Huili
GUO Yiyun
ZHANG Lei
Abstract：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 algo‐rithm is improved .Specifically ,it presents to get the average optimal solution for the position of each iteration instead of in‐dividual 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 .
Keywords：particle swarmchaotic PSOshrinkage factorvehicle routing problem
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 2106-2109,2116 )