| 带惯性权重的粒子群优化算法性能仿真 |
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| 引用本文： | 骆睿,周宁,赵舵. 带惯性权重的粒子群优化算法性能仿真[J]. 信息技术, 2008, 32(8) |
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| 作者姓名： | 骆睿 周宁 赵舵 |
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| 作者单位： | 电子科技大学通信与信息工程学院,成都,610054 |
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| 摘 要： | 粒子群优化算法是一种随机搜索算法,并能以较大概率收敛到全局最优,微粒群算法中关键参数的选择方法对算法特性有显著影响.文中针对微粒群算法中的加速常数、惯性权重、取值范围、种群规模的设置对算法基本性能的影响进行了分析.实验结果证明:选择适合的参数设置水平,能够获得稳健和高效的优化效果.
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| 关 键 词： | 优化 群体智能 粒子群算法 |
Simulation for particle swarm optimization algorithm |
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| LUO Rui,ZHOU Ning,ZHAO Duo. Simulation for particle swarm optimization algorithm[J]. Information Technology, 2008, 32(8) |
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| Authors: | LUO Rui ZHOU Ning ZHAO Duo |
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| Affiliation: | LUO Rui,ZHOU Ning,ZHAO Duo (School of Communication , Information Engineering,University of Electronic Science , Technology of China,Chengdu 610054,China) |
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| Abstract: | Particle swarm optimization algorithm is a random searching algorithm.It can converge to the global minima more probability.In particle swarm optimization algorithm, selection of key parameters has great influence on the algorithm effects. So this paper analyzes the effect of accelerating constants, inertia weight,range and swarm size. It is proved that robust and effective optimization can be achieved by setting the appropriate parameters. |
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| Keywords: | optimization swarm intelligence particle swarm algorithm |
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