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基于多核微机的微粒群并行算法
引用本文: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. DOI: 10.3778/j.issn.1002-8331.2010.13.010
作者姓名:陈华  范宜仁  邓少贵  李智强
作者单位:中国石油大学(华东),山东 东营 257061
基金项目:山东省自然科学基金No.Y2007F25;;中国石油大学优秀博士学位论文培育基金(No.B2007-05)~~
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  
收稿时间:2008-11-20
修稿时间:2009-1-4 

Multi-core parallel particle swarm optimization algorithm
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. DOI: 10.3778/j.issn.1002-8331.2010.13.010
Authors:CHEN Hua  FAN Yi-ren  DENG Shao-gui  LI Zhi-qiang
Affiliation:China University of Petroleum,Dongying,Shandong 257061,China
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 c...
Keywords:OpenMP  particle swarm optimization algorithm  multi-core parallel computation
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