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计算机工程 ›› 2009, Vol. 35 ›› Issue (22): 202-204. doi: 10.3969/j.issn.1000-3428.2009.22.069

• 人工智能及识别技术 • 上一篇    下一篇

基于多样性反馈的粒子群优化算法

焦 巍,刘光斌   

  1. (第二炮兵工程学院测试与控制工程系,西安 710025)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-11-20 发布日期:2009-11-20

Particle Swarm Optimization Algorithm Based on Diversity Feedback

JIAO Wei, LIU Guang-bin   

  1. (Department of Testing and Control Engineering, The Second Artillery Engineering College, Xi’an 710025)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-11-20 Published:2009-11-20

摘要: 利用粒子群多样性的反馈信息,给出带有粒子群多样性测度反馈控制的新惯性权值动态自适应调节方法,有效地维持进化初期的种群多样性,降低粒子群优化算法在进化初期发生早熟的风险,提高最优化解的精度,减小种群规模对优化精度的影响。几个典型函数的仿真结果以及与2种典型的惯性权值调节粒子群算法的比较结果表明了算法的有效性。

关键词: 粒子群优化, 多样性, 惯性权值

Abstract: A new method of adjusting inertial weight adaptively with diversity feedback control is proposed. The diversity of swarm is maintained especially in the early phase of iterations. The risk of premature convergence is reduced and the precision of the optimum is improved remarkably, the influence of the swarm size on an optimum is weakened. The efficiency of the algorithm is verified by the simulation results of three benchmark functions and the comparison with two adaptive inertial weight Particle Swarm Optimization(PSO) algorithms.

Key words: Particle Swarm Optimization(PSO), diversity, inertial weight

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