J4 ›› 2014, Vol. 41 ›› Issue (6): 100-105.doi: 10.3969/j.issn.1001-2400.2014.06.017

• 研究论文 • 上一篇    下一篇



  1. (1. 西安电子科技大学 数学与统计学院,陕西 西安  710071;
    2. 西安科技大学 理学院,陕西 西安  710054;
    3. 西安电子科技大学 计算机学院,陕西 西安  710071)
  • 收稿日期:2014-02-28 出版日期:2014-12-20 发布日期:2015-01-19
  • 通讯作者: 刘杰
  • 作者简介:刘杰(1977-), 男, 讲师, 西安电子科技大学博士研究生, E-mail: tears191@foxmail.com.
  • 基金资助:

    国家自然科学基金资助项目(61272119, 11301414, 11226173)

Central force optimization algorithm via clustering simplex search

LIU Jie1,2;WANG Yuping3   

  1. (1. School of Mathematics and Statistics, Xidian Univ., Xi'an  710071, China;
    2. College of Science, Xi'an University of Science and Technology, Xi'an  710054, China;
    3. School of Computer Science and Technology, Xidian Univ., Xi'an  710071, China)
  • Received:2014-02-28 Online:2014-12-20 Published:2015-01-19
  • Contact: LIU Jie



关键词: 中心引力优化, 聚类分析, 单纯形, 全局优化


An improved central force optimization (CFO) is proposed based on the clustering and simplex method for global optimization. The clustering simplex (CS) operator is introduced to a new algorithm in the evolution process. Vertices of simplex are selected by clustering methods, and a periodical migrating of the best individual is introduced by the CS operator. CS can get away from local converged points by virtue of CFO, and CFO can improve its local exploiting capability and effectively speed up the convergence under the help of CS. Experimental results show that the proposed hybrid CSCFO algorithm is better than other algorithms in convergent speed and searching precision.

Key words: central force optimization, cluster analysis, simplex, global optimization


  • TP301