| 基于微分模型的改进微粒群算法 |
| |
| 引用本文： | 崔志华,曾建潮. 基于微分模型的改进微粒群算法[J]. 计算机研究与发展, 2006, 43(4): 646-653 |
| |
| 作者姓名： | 崔志华 曾建潮 |
| |
| 作者单位： | 太原科技大学系统仿真与计算机应用研究所,太原,030024 |
| |
| 基金项目： | 重庆市应用基础研究基金 |
| |
| 摘 要： | 针对基本微粒群算法的微分模型，从解的存在惟一性角度出发，发现最大速度常数虽然能保证解的存在性，但却降低了算法的全局搜索性能．为了提高算法的计算效率，提出了一种不合最大速度常数的微分模型，该模型首先将速度向量与位置向量等同对待，两者同时对空间进行搜索，并讨论了该模型解的稳定性条件，给出了相应的改进微粒群算法，能有效地提高算法效率．仿真结果证明了算法的有效性．
|
| 关 键 词： | 微粒群算法 微分模型 速度向量 稳定性 |
| 收稿时间： | 2005-01-11 |
| 修稿时间： | 2005-01-112005-08-26 |
Modified Particle Swarm Optimization Based on Differential Model |
| |
| Cui Zhihua,Zeng Jianchao. Modified Particle Swarm Optimization Based on Differential Model[J]. Journal of Computer Research and Development, 2006, 43(4): 646-653 |
| |
| Authors: | Cui Zhihua Zeng Jianchao |
| |
| Affiliation: | Division of System Simulation and Computer Application, Taiyuan University of Science and Technology, Taiyuan 030024 |
| |
| Abstract: | Through mechanism analysis of differential model of particle swarm optimization, the effect of the maximum speed constant is analyzed and the results are shown that can guarantee the existence of solution, but decrease the global search capability. A new broaden differential model is proposed, which treats the velocity and position vectors equally and searches the space at the same time. And the stability condition is also discussed, Thus a new modified particle swarm optimization algorithm is given. The optimization computing of some examples is made to show that the new algorithm has better global search capacity and rapid convergence rate. |
| |
| Keywords: | particle swarm optimization differential model speed vector stability |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
