计算物理 ›› 2015, Vol. 32 ›› Issue (6): 693-700.

• 论文 • 上一篇    下一篇

粒子群算法在非线性系统应用中的早熟现象及其改进

肖媛, 崔国民, 彭富裕, 周静   

  1. 上海理工大学能源与动力工程学院, 上海 200093
  • 收稿日期:2014-11-11 修回日期:2015-04-14 出版日期:2015-11-25 发布日期:2015-11-25
  • 作者简介:肖媛(1991-),女,硕士研究生,研究方向为过程系统工程,E-mail:yxiao0606@yeah.net
  • 基金资助:
    国家自然科学基金(51176125);沪江基金研究基地专项(D14001)资助项目

An Improved Particle Swarm Optimization for Precocious Phenomenon in Nonlinear System Engineering

XIAO Yuan, CUI Guomin, PENG Fuyu, ZHOU Jing   

  1. School of Energy and Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Received:2014-11-11 Revised:2015-04-14 Online:2015-11-25 Published:2015-11-25

摘要: 通过分析粒子群算法早熟现象的机理,研究早熟收敛的本质,并提出一种克服粒子群算法早熟现象的局部"飞跃"策略.应用仿真及系统工程实例表明,该方法能有效地改善粒子群算法在非线性全局优化上的早熟问题,提高了粒子群算法的全局搜索能力.

关键词: 粒子群算法, 早熟收敛, 系统工程, 局部"飞跃"策略

Abstract: By analyzing mechanism of premature phenomenon in particle swarm optimization (PSO), we found nature of premature convergence and proposed a "leap" strategy to jump out of local minimum, making halted particles "renewed" when they are trapped into a local optimum. The strategy is applied to nonlinear programming and results are encouraging. The improved PSO solves efficiently premature convergence of the algorithm applying in nonlinear optimizations and improves global search ability of PSO.

Key words: particle swarm optimization, premature converge, systems engineering, "leap"strategy

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