摘要
通过引入混沌来影响粒子速度的更新,构造出一种混沌粒子群优化算法.其主要思想是用混沌迭代引导个体进一步优化,从而避免群体陷入局部最优,而且收敛速度得到加快.通过对三个测试函数以及平面选址问题的求解,验证该算法具有非常好的性能.
A kind of particle swarm optimization algorithm with chaos is constructed by adding chaos to influence the update of the velocities of particles. The main idea is to guide individual further optimization by chaos iterations. The technique can either avoid that the population trap into the local optimum or accelerate the convergence rate. It has better application in planar location problem.
出处
《河南科学》
2006年第5期707-710,共4页
Henan Science
关键词
粒子群算法
混沌
随机搜索
测试函数
平面选址
particle swarm algorithm
chaos
stochastic searching
test function
planar location problem
