Label entropy‐based cooperative particle swarm optimization algorithm for dynamic overlapping community detection in complex networks

2021 ◽  
Author(s):  
Wenchao Jiang ◽  
Shucan Pan ◽  
Chaohai Lu ◽  
Zhiming Zhao ◽  
Sui Lin ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Complex Networks ◽  
Community Detection ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Overlapping Community Detection ◽  
Overlapping Community

A Memetic Particle Swarm Optimization Algorithm for Community Detection in Complex Networks

2016 ◽  
Vol 30 (02) ◽  
pp. 1659003 ◽  
Author(s):  
Cheng Zhang ◽  
Xinhong Hei ◽  
Dongdong Yang ◽  
Lei Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Complex Networks ◽  
Community Detection ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Optimization Methods ◽  
Limit Problem ◽  
Resolution Limit ◽  
Swarm Optimization

In recent years, community detection has become a hot research topic in complex networks. Many of the proposed algorithms are for detecting community based on the modularity Q. However, there is a resolution limit problem in modularity optimization methods. In order to detect the community structure more effectively, a memetic particle swarm optimization algorithm (MPSOA) is proposed to optimize the modularity density by introducing particle swarm optimization-based global search operator and tabu local search operator, which is useful to keep a balance between diversity and convergence. For comparison purposes, two state-of-the-art algorithms, namely, meme-net and fast modularity, are carried on the synthetic networks and other four real-world network problems. The obtained experiment results show that the proposed MPSOA is an efficient heuristic approach for the community detection problems.

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