| 粒子群优化算法发展综述 |
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| 引用本文： | 董元,王勇,易克初. 粒子群优化算法发展综述[J]. 商洛学院学报, 2006, 20(4): 28-33 |
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| 作者姓名： | 董元 王勇 易克初 |
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| 作者单位： | 西安电子科技大学综合业务网国家重点实验室,陕西,西安,710071 |
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| 摘 要： | 粒子群优化（PSO）算法是一种源于人工生命和演化计算理论的优化技术．PSO通过粒子搜寻自身的个体最好解和整个粒子群的全局最好解来更新完成优化．该算法原理简单，所需参数枝少，易于实现，目前已经应用到很多领域．文章阐述了基本PSO的原理。给出了各种改进技术，并展望了PSO的发展方向。
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| 关 键 词： | 进化算法 粒子群优化 混合算法 自适应 异步模式 |
| 文章编号： | 1008-3030（2006）04-0028-06 |
| 收稿时间： | 2006-09-16 |
| 修稿时间： | 2006-09-16 |
An overview of the development of particle swarm optimization |
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| DONG Yuan,WANG Yong,YI Ke-chu. An overview of the development of particle swarm optimization[J]. Journal of Shangluo University, 2006, 20(4): 28-33 |
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| Authors: | DONG Yuan WANG Yong YI Ke-chu |
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| Abstract: | Particle swarm optimization(PSO)algorithm as one of optimization techniques comes from artificial life and theory of evolutionary algorithms.It can be gathered from the update equations that the trajectory of each particle is influenced in a direction determined by the previous velocity and the location of each particle's previous position and the swarm's overall best position.With its simple principle,limited parameter and its easy implementation,it has been used widely now in many areas.This paper illustrates the foundational theory of PSO,enumerates various evolutionary technologies and previews the development of PSO. |
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| Keywords: | evolutionary algorithm particle swarm optimization hybrid algorithm adaptive asynchronous model |
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