Hybrid particle swarm optimization algorithm merging simulated annealing and chaos

doi:10.3778/j.issn.1002-8331.2009.07.017

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (7): 52-55.DOI: 10.3778/j.issn.1002-8331.2009.07.017

• 研究、探讨 • Previous Articles Next Articles

Hybrid particle swarm optimization algorithm merging simulated annealing and chaos

JIA Song-wei,GAO Yue-lin

Research Institute of Information and System Science，North National University，Yinchuan 750021，China

Received:2008-08-29 Revised:2008-11-03 Online:2009-03-01 Published:2009-03-01
Contact: JIA Song-wei

融合模拟退火和混沌的混合粒子群算法

贾松卫,高岳林

北方民族大学信息与系统科学研究所，银川 750021

通讯作者: 贾松卫

Abstract

Abstract: To improve the global search ability of Particle Swarm Optimization algorithm（PSO），simulated annealing idea is applied in selecting PSO’s inertia weight and chaos algorithm is merged into PSO according to the properties of chaos to make adaptively chaotic mutation for premature population.The numerical experiments demonstrate that the produced hybrid PSO algorithm has the ability to balance local optimizing and global optimizing and improves the ability of global optimization and the precision of computation.

Key words: Particle Swarm Optimization（PSO）, simulated annealing, chaos

摘要： 为了改善粒子群算法的全局搜索能力，把模拟退火思想融于惯性权重的选取之中，再利用混沌运动的特性来融合混沌算法，对早熟的种群进行自适应混沌变异。数值仿真结果表明，所产生的混合粒子群算法能更好地平衡局部寻优和全局寻优，提高了全局寻优的能力和计算的精度。

关键词: 粒子群优化, 模拟退火, 混沌

JIA Song-wei,GAO Yue-lin. Hybrid particle swarm optimization algorithm merging simulated annealing and chaos[J]. Computer Engineering and Applications, 2009, 45(7): 52-55.

贾松卫,高岳林. 融合模拟退火和混沌的混合粒子群算法[J]. 计算机工程与应用, 2009, 45(7): 52-55.

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Hybrid particle swarm optimization algorithm merging simulated annealing and chaos

融合模拟退火和混沌的混合粒子群算法

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