Community Detection Using Differential Evolution Algorithm with Multiple Objective Function

Abstract

In this paper, we conducted an experiment on differential evolution algorithm with multiple objective functions for community detection. The community detection in social networks is an important problem in many scientific fields. Differential algorithms use modularity as a fitness function in general. In this work, we have used different objective function such as conductance, normalized cut, Average degree and two well known datasets such as Zachary Karate Club and American College Football Network. We evaluated DECD on several artificial and real-world social and biological networks using multiple objective functions. After result analysis shows that DECD with multiple objective functions has very competitive performance compared with other community detection algorithms.