Cooperative approach to Quantum-behaved Particle Swarm Optimization

doi:10.3778/j.issn.1002-8331.2010.04.012

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (4): 39-42.DOI: 10.3778/j.issn.1002-8331.2010.04.012

• 研究、探讨 • Previous Articles Next Articles

Cooperative approach to Quantum-behaved Particle Swarm Optimization

KANG Yan¹，FENG Hai-peng²，XU Wen-bo³，YANG Yan-ping¹

1.Department of Computer Science，Hebei Normal University of Science & Technology，Qinhuangdao，Hebei 066004，China
2.Key Lab of Network Controlling，Chongqing University of Posts and Telecommunications，Chongqing 400065，China
3.School of Information Technology，Southern Yangtze University，Wuxi，Jiangsu 214122，China

Received:2008-08-12 Revised:2009-01-12 Online:2010-02-01 Published:2010-02-01
Contact: KANG Yan

合作的具有量子行为粒子群优化算法

康燕¹，冯海朋²，须文波³，杨燕萍¹

1.河北科技师范学院计算机系，河北秦皇岛 066004
2.重庆邮电大学网络控制重点实验室，重庆 400065
3.江南大学信息学院，江苏无锡 214122

通讯作者: 康燕

Abstract

Abstract: An improvement method for Quantum-behaved Particle Swarm Optimization algorithm（QPSO），that is，Cooperative Quantum-behaved Particle Swarm Optimization（CQPSO） algorithm，is introduced by analyzing deeply the QPSO.Experiments for several benchmark problems show that CQPSO can overcome the fault of QPSO and increase the optimization power of the particle swarm.

摘要： 通过对具有量子行为的粒子群优化（Quantum-behaved Particle Swarm Optimization，QPSO）算法深入分析，把协作机制引入到QPSO算法中，提出了协作的具有量子行为的粒子群优化（Cooperative Quantum-behaved Particle Swarm Optimization）算法，并详细阐述了这种算法的主要思想。测试结果表明，这种改进算法能够克服QPSO算法中的不足，增强了粒子群的优化能力。

CLC Number:

TP301.6

KANG Yan¹，FENG Hai-peng²，XU Wen-bo³，YANG Yan-ping¹. Cooperative approach to Quantum-behaved Particle Swarm Optimization[J]. Computer Engineering and Applications, 2010, 46(4): 39-42.

康燕¹，冯海朋²，须文波³，杨燕萍¹. 合作的具有量子行为粒子群优化算法[J]. 计算机工程与应用, 2010, 46(4): 39-42.

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Cooperative approach to Quantum-behaved Particle Swarm Optimization

合作的具有量子行为粒子群优化算法

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