J4 ›› 2013, Vol. 40 ›› Issue (3): 205-211.doi: 10.3969/j.issn.1001-2400.2013.03.031

• 研究论文 • 上一篇    下一篇



  1. (1. 西安电子科技大学 计算机学院,陕西 西安  710071;
    2. 河南大学 计算机与信息工程学院,河南 开封  475004)
  • 收稿日期:2012-02-17 出版日期:2013-06-20 发布日期:2013-07-29
  • 通讯作者: 陈国强
  • 作者简介:陈国强(1977-),男,西安电子科技大学博士研究生,E-mail: chengq08@163.com.
  • 基金资助:


Revealing of  the hierarchy community of the complex network by decomposition multi-objective optimization

CHEN Guoqiang1,2;WANG Yuping1   

  1. (1. School of Computer Science and Technology, Xidian Univ., Xi'an  710071, China;
    2. School of Computer and Information Engineering, Henan Univ., Kaifeng  475004, China)
  • Received:2012-02-17 Online:2013-06-20 Published:2013-07-29
  • Contact: CHEN Guoqiang



关键词: 复杂网络, 社区检测, 多目标优化, 层次结构


A new algorithm for community detection of complex networks is proposed. The problem of community detection is considered as multi-objective optimization problem. Tradeoff among multi-objectives realizes the detection of the community structure in a wider spread space, the disadvantages of the traditional single optimization algorithm is overcome. The MOEA/D framework is adopted and the Tchebycheff decomposition technique is used. A simulated annealing based weighted-sum method is used to perform local search which can expand the search scope, and not easily fall into local optimal solution. Finally, simulation experiments are done to test the algorithm using artificial and reality networks. The results show that, compared with existing algorithms, the algorithm has a higher detection accuracy and a small amount of computation, and can reveal the hierarchy community structure of the complex network by Pareto optimal solutions.

Key words: complex networks, community detection, multi objective optimization, hierarchy structure


  • TP393