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分合粒子群优化算法


  摘 要:基于社会系统中普遍存在“分久必合,合久必分”的现象,提出了基于分合思想的粒子群优化算法。分策略提高了演化群体的多样性,克服了粒子群优化算法局部收敛的缺陷。合策略吸取了不同群体的优良特性,提高了算法的全局搜索能力。函数优化的仿真结果证明了算法的有效性。

  关键词:粒子群优化算法; 早熟; 函数优化; 分合策略

  中图分类号:TP301.6文献标志码:A

  文章编号:1001-3695(2010)06-2024-02

  doi:10.3969/j.issn.1001-3695.2010.06.006

   Particle swarm optimization based on division and union strategy

  CHEN Jian-chao1, HU Gui-wu1,2,3

  (1. School of Mathematics & Computational Science, Guangdong University of Business Studies, Guangzhou 510320, China; 2. Key Laboratory of Data Engineer & Knowledge Engineer for Ministry ofEducation, Beijing 100872, China; 3. School of Information, Renmin University of China, Beijing 100872, China)

  Abstract:Basing on a ubiquitous scheme:the world, long divided, must reunite; long united, must divide, which was reported to well represent the nature of social evolution process, this paper proposed divided and united particle swarm optimization. In the new algorithm, division strategy was able to improve the diversity of population, which overcame the local convergence of PSO.Union strategy was able to combine the merit of different population and improved its global research ability. Finally, used the novel algorithm to solve function optimization problem. The result shows that the algorithm is effective.

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