| 粒子群优化算法 |
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| 引用本文： | 崔长彩,李兵,张认成. 粒子群优化算法[J]. 华侨大学学报(自然科学版), 2006, 27(4): 343-347 |
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| 作者姓名： | 崔长彩 李兵 张认成 |
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| 作者单位： | 华侨大学机电及自动化学院,福建,泉州,362021;华侨大学机电及自动化学院,福建,泉州,362021;华侨大学机电及自动化学院,福建,泉州,362021 |
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| 基金项目： | 福建省青年科技人才创新基金资助项目(2005J030) |
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| 摘 要： | 论述粒子群优化算法(PSO)的基本原理、特点、实现步骤,以及PSO的各种改进技术,包括基于PSO参数的改进技术(主要是惯性权重)、基于遗传算法进化机理的改进技术(受遗传算法启发提出的带交叉算子的PSO、带变异算子的PSO、带选择算子的PSO),以及其他算法融合的改进技术(模拟退火PSO、免疫PSO、混沌PSO),并总结PSO热点研究问题.
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| 关 键 词： | 粒子群 优化算法 遗传算法 惯性权重 |
| 文章编号： | 1000-5013（2006）04-0343-05 |
| 收稿时间： | 2006-03-08 |
| 修稿时间： | 2006-03-08 |
Particle Swarm Optimization |
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| Cui Changcai,Li Bing,Zhang Rencheng. Particle Swarm Optimization[J]. Journal of Huaqiao University(Natural Science), 2006, 27(4): 343-347 |
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| Authors: | Cui Changcai Li Bing Zhang Rencheng |
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| Affiliation: | College of Mechanical Engineering and Automation, Huaqiao University, 362021, Quanzhou, China |
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| Abstract: | The particle swarm optimization(PSO) was introduced about its fundamentals,characteristics,implementation steps,and its improved versions,which were based on the parameter updating(mainly inertia weight),or illuminated by the evolutionary principles of genetic algorithm(GA)(e.g. PSOs with crossover,mutation or selection operator),or combined with other algorithms(e.g.simulating annealing PSO,immune PSO,chaotic PSO), and the hot topics of PSO were summarized too. |
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| Keywords: | particle swarm optimization algorithm genetic algorithm inertia weigth |
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