| 改进的吸引扩散微粒群算法 |
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| 引用本文： | 陈保娣,曾建潮.改进的吸引扩散微粒群算法[J].控制理论与应用,2010,27(4):451-456. |
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| 作者姓名： | 陈保娣 曾建潮 |
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| 作者单位： | 太原科技大学复杂系统与计算智能实验室,山西太原,030024 |
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| 基金项目： | 教育部重点科研资助项目(204018); 山西省自然科学基金资助项目(2008011027-2). |
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| 摘 要： | 为了避免微粒群算法存在的过早收敛问题, 在ARPSO的基础之上, 提出了一个简单的种群多样性度量函数和微粒最好飞行方向的概念, 引入了变异策略, 从而实现了一种改进的吸引扩散微粒群算法MARPSO, 并从理论上分析了MARPSO的局部收敛性和全局收敛性. 对四个经典函数进行了仿真测试, 测试结果表明: 与基本微粒群算法BPSO和ARSPO相比, 该算法能够有效的提高种群多样性, 并且具有较高的收敛速度.
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| 关 键 词： | 微粒群算法 种群多样性 微粒最好飞行方向 收敛 |
| 收稿时间： | 2008/12/10 0:00:00 |
| 修稿时间： | 2009/4/26 0:00:00 |
Modified attractive and repulsive particle swarm optimization |
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| CHEN Bao-di and ZENG Jian-chao.Modified attractive and repulsive particle swarm optimization[J].Control Theory & Applications,2010,27(4):451-456. |
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| Authors: | CHEN Bao-di and ZENG Jian-chao |
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| Affiliation: | Complex System and Computational Intelligence Laboratory/a>;Taiyuan University of Science and Technology/a>;Taiyuan Shanxi 030024/a>;China |
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| Abstract: | To avoid the premature convergence,based on the attractive and repulsive particle swarm optimizer(ARPSO),we propose a novel measure function for the population diversity,and a new concept of the particle's best flight direction.A modified ARPSO(MARPSO)is proposed by introducing a mutation strategy.Moreover,theoretical analysis has been made to prove that the algorithm can guarantee local convergence and global convergence.By comparing the simulation results of four classic testing functions with basic PSO(B... |
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| Keywords: | particle swarm optimization swarm diversity particle's best flight direction convergence |
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