Multi-core parallel particle swarm optimization algorithm

doi:10.3778/j.issn.1002-8331.2010.13.010

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (13): 34-36.DOI: 10.3778/j.issn.1002-8331.2010.13.010

• 研究、探讨 • Previous Articles Next Articles

Multi-core parallel particle swarm optimization algorithm

CHEN Hua，FAN Yi-ren，DENG Shao-gui，LI Zhi-qiang

China University of Petroleum，Dongying，Shandong 257061，China

Received:2008-11-20 Revised:2009-01-04 Online:2010-05-01 Published:2010-05-01
Contact: CHEN Hua

基于多核微机的微粒群并行算法

陈华，范宜仁，邓少贵，李智强

中国石油大学（华东），山东东营 257061

通讯作者: 陈华

Abstract

Abstract: A nonlinear adjustment strategy for inertia weight which is based on logistic model is proposed，and multi-core parallel computation of particle swarm optimization algorithm is realized which uses OpenMP multithread programming.Five function of BenchMark function set is tested.The results show that success rates and convergence times of algorithm which uses nonlinear adjustment strategy are superior to linear adjustment strategy.The calculation speed is improved which is based on OpenMP multi-core parallel computation of particle swarm optimization algorithm.

Key words: OpenMP, particle swarm optimization algorithm, multi-core parallel computation

摘要： 提出了一种基于Logistic模型的惯性权重非线性调整策略，采用OpenMP多线程编程，在微机上实现了微粒群算法的多核并行计算。通过对BenchMark测试函数集中的5个函数进行测试，试验结果表明，采用基于Logistic模型的惯性权重非线性调整策略在算法成功率和收敛代数都优于线性调整策略，而基于OpenMP的微粒群多核并行计算使得计算速度得到提高。

关键词: OpenMP, 微粒群优化算法, 多核并行计算

CLC Number:

TP301.6

CHEN Hua，FAN Yi-ren，DENG Shao-gui，LI Zhi-qiang. Multi-core parallel particle swarm optimization algorithm[J]. Computer Engineering and Applications, 2010, 46(13): 34-36.

陈华，范宜仁，邓少贵，李智强. 基于多核微机的微粒群并行算法[J]. 计算机工程与应用, 2010, 46(13): 34-36.

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Multi-core parallel particle swarm optimization algorithm

基于多核微机的微粒群并行算法

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