计算机工程Issue(7)：202-206,5.DOI:10.3969/j.issn.1000-3428.2014.07.040
双心扰动量子粒子群优化算法研究
Research on QPSO Algorithm of Double Core Disturbance
王安龙 1何建华 1陈松 1刘怀远1
作者信息
- 1. 西北工业大学电子信息学院，西安 710000
- 折叠
摘要
Abstract
Aiming at the problem of the premature convergence of Quantum Particle Swarm Optimization(QPSO) algorithm. This paper introduces a double core disturbance mutation mechanism. It uses adaptive Cauchy mutation to mutate the potential energy of the particle center and the center of gravity of the particle swarm and make full use of the guiding ability of the two centers in the late part of evolution. It adopts four typical functions to conduct simulation experiment, results show that double core disturbances mutation mechanism optimization is better than the strategy of only potential energy center, the center of gravity or global optimal mutation at least 36.42%, and the optimization results improve at least 32.84%for multimodal function optimization.关键词
量子粒子群优化算法/势能中心/全局最好位置/柯西变异/函数优化Key words
Quantum Particle Swarm Optimization(QPSO) algorithm/potential energy center/global best position/Cauchy mutation/function optimization分类
信息技术与安全科学引用本文复制引用
王安龙,何建华,陈松,刘怀远..双心扰动量子粒子群优化算法研究[J].计算机工程,2014,(7):202-206,5.
