| 一种新改进的粒子群优化算法 |
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| 引用本文： | 吴烈阳,俞智慧,万佳,段志翔.一种新改进的粒子群优化算法[J].适用技术之窗,2011(11):17-20. |
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| 作者姓名： | 吴烈阳 俞智慧 万佳 段志翔 |
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| 作者单位： | [1]江西省高速公路联网管理中心,江西南昌330003 [2]上饶师范学院数学与计算机科学学院,江西上饶334001 [3]江西省通用技术工程学校,江西九江330306 [4]江西科技职业学院,江西南昌330200 |
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| 摘 要： | 由于粒子群优化算法对多极值复杂问题求解时容易陷入局部极值,提出一种新改进的粒子群优化算法。该改进算法是将粒子群进化过程分为两个不同的阶段,每个阶段应用不同的进化模型,通过结合这两种进化模型的各自优点有效地降低群体陷入局部最优。由仿真实验结果可知,对于复杂多极值函数优化问题,本文算法比标准粒子群优化算法的全局寻优能力更强。
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| 关 键 词： | 粒子群优化算法 局部极值 进化模型 |
An Improved Particle Swarm Optimization |
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| Wu Lieyang Yu Zhihui Wan Jia Duan Zhixiang.An Improved Particle Swarm Optimization[J].Science & Technology Plaza,2011(11):17-20. |
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| Authors: | Wu Lieyang Yu Zhihui Wan Jia Duan Zhixiang |
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| Affiliation: | Wu Lieyang Yu Zhihui Wan Jia Duan Zhixiang(1.Highway Network Management Center of Jiangxi Province,Jiangxi Nanchang 330003; 2.School of Mathematics and Computer Science,Shangrao Normal University,Jiangxi Shangrao 334001; 3.Jiangxi General Technical Engineering School,Jiangxi Jiujiang330306; 4.Jiangxi University of Science And Technology,Jiangxi Nanchang 330200) |
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| Abstract: | Considering that the standard PSO easily falls into local optimization when it solves the multi-extremum problems,an improved PSO algorithm is proposed.In this algorithm,the evolution process is divided into two stages,while each stage uses a different model,so the possibility of getting local extreme value is reduced by make full use of the respective advantages of the two evolution model.The results of simulation show that the proposed algorithm in the paper has the better optimization performance than the standard PSO when solving the multi-extremum problems. |
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| Keywords: | Particle Swarm Optimization Local Optimization Evolution Model |
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