A Genetic Algorithm with Local Search Strategy for Improved Detection of Community Structure

作者：Li Shuzhuo; Chen Yinghui; Du Haifeng; Feldman Marcus W^*

来源：Complexity, 2010, 15(4): 53-60.

DOI：10.1002/cplx.20300

• network structure
• modularity
• genetic algorithm
• small-world phenomena

On the basis of modularity optimization, a genetic algorithm is proposed to detect, community structure in networks by defining a local search operator: The local search operator emphasizes two features: one is that the connected nodes in a network should be located in the same community, while the other is "local selection" inspired by the mechanisms of efficient message delivery underlying the small-world phenomenon. The results of community detection for some classic networks, such as Ucinet and Pajek networks, indicate that our algorithm. achieves better community structure than. other methodologies based on modularity optimization, such. as the algorithms based on betweenness analysis, simulated annealing or Tasgin and Bingol's genetic algorithm.

• 出版日期2010-4
• 单位西安交通大学