Improved velocity of PSO algorithm and adaptive mutation

doi:10.3778/j.issn.1002-8331.2010.13.014

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (13): 47-50.DOI: 10.3778/j.issn.1002-8331.2010.13.014

• 研究、探讨 • Previous Articles Next Articles

Improved velocity of PSO algorithm and adaptive mutation

LI Hui-rong^1，2，GAO Yue-lin²

1.Department of Mathematics and Computation Science，Shangluo University，Shangluo，Shaanxi 726000，China
2.Research Institute of Information and System Science，North National University，Yinchuan 750021，China

Received:2008-11-07 Revised:2009-01-22 Online:2010-05-01 Published:2010-05-01
Contact: LI Hui-rong

粒子群优化的速度方程改进与自适应变异策略

李会荣^1，2，高岳林²

1.商洛学院数学与计算科学系，陕西商洛 726000
2.北方民族大学信息与系统科学研究所，银川 750021

通讯作者: 李会荣

Abstract

Abstract: An Improved Particle Swarm Optimization（IPSO） algorithm is proposed by improving the standard PSO’s velocity equation.The new algorithm reduces the control parameters，introduces random adjustment factor，and generates the cognitive ability and social cognitive ability of the particle randomly in a certain range.By judging the local convergence，when PSO gets into the local convergence，IPSO can carry out stochastic mutation on individual optimal particle.The experimental results demonstrate that the new algorithm can overcome premature convergence，and has better global searching and performance.

Key words: particle swarm optimization, random adjustment factor, stochastic mutation

摘要： 对基本粒子群优化算法的速度方程进行了改进，减少了控制参数，引入随机调节因子，使得粒子的自我认知能力和社会认知能力在一定范围内随机产生，同时对个体最优粒子进行自适应随机变异，由此构造出一种改进的粒子群优化算法。数值结果表明新算法能够克服早熟收敛，具有更好的性能和全局搜索能力。

关键词: 粒子群优化, 随机调节因子, 随机扰动

CLC Number:

TP18

LI Hui-rong^1，2，GAO Yue-lin². Improved velocity of PSO algorithm and adaptive mutation[J]. Computer Engineering and Applications, 2010, 46(13): 47-50.

李会荣^1，2，高岳林². 粒子群优化的速度方程改进与自适应变异策略[J]. 计算机工程与应用, 2010, 46(13): 47-50.

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Improved velocity of PSO algorithm and adaptive mutation

粒子群优化的速度方程改进与自适应变异策略

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