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| 粒子群算法求解连续优化问题的性能分析 | |
| 引用本文： | 镡铁春,刘伯颖,吴敬松,李娜娜.粒子群算法求解连续优化问题的性能分析[J].微计算机应用,2008,29(10). |
| 作者姓名： | 镡铁春 刘伯颖 吴敬松 李娜娜 |
| 作者单位： | 1. 河北工业大学国际交流教育学院,天津,300130 2. 河北工业大学教务处,天津,300130 3. 河北工业大学,计算机科学与软件学院,天津,300130 |
| 摘 要： | 粒子群优化(PSO)算法是一类有效的随机全局优化技术,适用于求解连续优化问题.它利用一个粒子群搜索解空间,通过粒子间的相互作用发现复杂搜索空间中的最优区域.本文介绍了基本的PSO算法,使用3类代表性的标准测试函数对粒子群算法进行了实验分析,并进一步讨论了PSO算法的寻优性能,提出了PSO求解连续优化问题的性能分析策略. |
| 关 键 词： | 粒子群 函数优化 群集智能 |
The Performance Analysis of Particle Swarm Optimization for Solving Continuous Optimization Problem |
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| CHAN Tiechun,LIU Boying,WU Jingsong,LI Nana.The Performance Analysis of Particle Swarm Optimization for Solving Continuous Optimization Problem[J].Microcomputer Applications,2008,29(10). | |
| Authors: | CHAN Tiechun LIU Boying WU Jingsong LI Nana |
| Abstract: | Particle swarm algorithm is a stochastic global optimization technique and it is fit for function optimization.The particle swarm algorithm find optimal regions of complex search spaces through the interaction of individuals in a population of particles.In this paper,classical particle swarm optimization algorithm is introduced.Furthermore results of experiments on three benchmark functions are shown and they demonstrate the efficiency of PSO in different ways. |
| Keywords: | particle swarm function optimization swarm intelligence |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |