An improved memetic algorithm for community detection in complex networks

Author

Gong, Maoguo ; Cai, Qing ; Li, Yangyang ; Ma, Jingjing

Author_Institution

Key Lab. of Intell. Perception & Image Understanding of Minist. of Educ., Xidian Univ., Xi´´an, China

fYear

2012

fDate

10-15 June 2012

Firstpage

1

Lastpage

8

Abstract

There is an increasing recognition on community detection in complex networks in recent years. In this study, we improve a recently proposed memetic algorithm for community detection in networks. By introducing a Population Generation via Label Propagation (PGLP) tactic, an Elitism Strategy (ES) and an Improved Simulated Annealing Combined Local Search (ISACLS) strategy, the improved memetic algorithm called (iMeme-Net) is put forward for solving community detection problems. Experiments on both computer-generated and real-world networks show the effectiveness and the multi-resolution ability of the proposed method.

Keywords

complex networks; network theory (graphs); simulated annealing; social sciences; ISACLS strategy; PGLP tactic; community detection; complex networks; elitism strategy; iMeme-Net; improved memetic algorithm; improved simulated annealing combined local search; label propagation; multiresolution ability; population generation; Benchmark testing; Biological cells; Clustering algorithms; Communities; Partitioning algorithms; Simulated annealing; community detection; elitism strategy; label propagation; memetic algorithm; simulated annealing;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation (CEC), 2012 IEEE Congress on

Conference_Location

Brisbane, QLD

Print_ISBN

978-1-4673-1510-4

Electronic_ISBN

978-1-4673-1508-1

Type

conf

DOI

10.1109/CEC.2012.6252971

Filename

6252971