DocumentCode :
2780774
Title :
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
Link To Document :
بازگشت