Double swarm variation particle swarm optimization

doi:10.3778/j.issn.1002-8331.2010.18.012

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (18): 35-37.DOI: 10.3778/j.issn.1002-8331.2010.18.012

• 研究、探讨 • Previous Articles Next Articles

Double swarm variation particle swarm optimization

PENG Xin，MA Lin-hua，WANG Jun-pan，SU Qiang

Department of Aeronautical Electronics Engineering，Engineering College，Air Force Engineering University，Xi’an 710038，China

Received:2009-01-07 Revised:2009-03-25 Online:2010-06-21 Published:2010-06-21
Contact: PENG Xin

双种群变异粒子群算法

彭鑫，马林华，王俊攀，苏强

空军工程大学工程学院航空电子工程系，西安 710038

通讯作者: 彭鑫

Abstract

Abstract: By the usage of the aberrance mechanism’s character of enhancing the global optimization-searching abilities，a Double swarm Variation Particle Swarm Optimization（DVPSO） algorithm based on the fast convergence of the PSO algorithm whose inertia-value is linearly descending is presented.The algorithm is contrasted with other PSO algorithm，and the simulation result shows that its performance is excellent.

Key words: Double swarm Variation Particle Swarm Optimization（DVPSO）, Auto-adapted Escaping Particle Swarm Optimization（AEPSO）, genetic algorithm

摘要： 利用变异机制可以增加遗传算法全局寻优能力的特性，结合惯性权值线性递减PSO算法具有较快收敛速度的优点，提出了一种双种群变异PSO算法，对该算法与其他PSO算法进行了比较，仿真结果表明其性能优越。

关键词: 双种群变异粒子群算法（DVPSO）, 自适应逃逸粒子群算法（AEPSO）, 遗传算法

CLC Number:

TP18

PENG Xin，MA Lin-hua，WANG Jun-pan，SU Qiang. Double swarm variation particle swarm optimization[J]. Computer Engineering and Applications, 2010, 46(18): 35-37.

彭鑫，马林华，王俊攀，苏强. 双种群变异粒子群算法[J]. 计算机工程与应用, 2010, 46(18): 35-37.

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Double swarm variation particle swarm optimization

双种群变异粒子群算法

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