A genetic algorithm for community detection in complex networks

作者：Li Yun^*; Liu Gang; Lao Song yang

来源：Journal of Central South University (English Edition), 2013, 20(5): 1269-1276.

DOI：10.1007/s11771-013-1611-y

• complex networks
• community detection
• genetic algorithm
• matrix encoding
• nodes similarity

A new genetic algorithm for community detection in complex networks was proposed. It adopts matrix encoding that enables traditional crossover between individuals. Initial populations are generated using nodes similarity, which enhances the diversity of initial individuals while retaining an acceptable level of accuracy, and improves the efficiency of optimal solution search. Individual crossover is based on the quality of individuals' genes; all nodes unassigned to any community are grouped into a new community, while ambiguously placed nodes are assigned to the community to which most of their neighbors belong. Individual mutation, which splits a gene into two new genes or randomly fuses it into other genes, is non-uniform. The simplicity and effectiveness of the algorithm are revealed in experimental tests using artificial random networks and real networks. The accuracy of the algorithm is superior to that of some classic algorithms, and is comparable to that of some recent high-precision algorithms.

• 出版日期2013-5
• 单位中国人民解放军国防科学技术大学