[1]钱伟懿,李明.依概率收敛的改进粒子群优化算法[J].智能系统学报,2017,(04):511-518.[doi:10.11992/tis.201610004]
 QIAN Weiyi,LI Ming.Improved particle swarm optimization algorithmwith probability convergence[J].CAAI Transactions on Intelligent Systems,2017,(04):511-518.[doi:10.11992/tis.201610004]
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依概率收敛的改进粒子群优化算法(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
期数:
2017年04期
页码:
511-518
栏目:
出版日期:
2017-08-25

文章信息/Info

Title:
Improved particle swarm optimization algorithmwith probability convergence
作者:
钱伟懿 李明
渤海大学 数理学院, 辽宁 锦州 121013
Author(s):
QIAN Weiyi LI Ming
College of Mathematics and Physics, Bohai University, Jinzhou 121013, China
关键词:
粒子群优化算法随机优化算法变异算子依概率收敛全局优化进化计算启发式算法高斯分布
Keywords:
particle swarm optimizationstochastic optimization algorithmmutation operatorprobability convergenceglobal optimizationevolutionary computationheuristic algorithmGaussian distribution
分类号:
TP301.6
DOI:
10.11992/tis.201610004
摘要:
粒子群优化算法是一种随机优化算法,但它不依概率1收敛到全局最优解。因此提出一种新的依概率收敛的粒子群优化算法。在该算法中,首先引入了具有探索和开发能力的两个变异算子,并依一定概率对粒子当前最好位置应用这两个算子,然后证明了该算法是依概率1收敛到ε-最优解。最后,把该算法应用到13个典型的测试函数中,并与其他粒子群优化算法比较,数值结果表明所给出的算法能够提高求解精度和收敛速度。
Abstract:
The particle swarm optimization (PSO) algorithm is a stochastic optimization algorithm that does not converge to a global optimal solution on the basis of probability 1. In this paper, we present a new probability-based convergent PSO algorithm that introduces two mutation operators with exploration and exploitation abilities, which are applied to the previous best position of a particle with a certain probability. This algorithm converges to the-optimum solution on the basis of probability 1.We applied the proposed algorithm in 13 typical test functions and compared its performance with that of other PSO algorithms. Our numerical results show that the proposed algorithm can improve solution precision and convergence speed.

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备注/Memo

备注/Memo:
收稿日期:2016-10-05。
基金项目:国家自然科学基金项目(11371071);辽宁省教育厅科学研究项目(L2013426).
作者简介:钱伟懿,男,1963年生,教授,博士,主要研究方向为智能计算、优化理论与方法,主持国家自然科学基金项目1项。发表学术论文60余篇,出版专著3部;李明,男,1991年生,硕士研究生,主要研究方向为智能计算。
通讯作者:钱伟懿,E-mail:qianweiyi2008@163.com.
更新日期/Last Update: 2017-08-25