Detecting Community Structure in Networks Based on Ant Colony Optimization

Community structure is a nature characteristic of many real networks. The problem of detecting and characterizing the community structure has attracted considerable recent attention. In this paper, we present a new algorithm based on ant colony optimization to detect community structure in networks. In the algorithm, artificial ants are used to travel on a logical digraph to construct solutions of community detection. Each ants chooses its path according to the pheromone and heuristic information on each path. We define an associate degree and use it as the heuristic information. The quality of solution obtained by each ant is measured by its modularity. The algorithm is tested on synthetic and real world networks. The experimental results show that our algorithm can achieve higher quality results than other methods. Keywords-component; detecting community structure; ant colony optimization;