Community finding in dynamic networks using a genetic algorithm improved via a hybrid immigrants scheme

Due to the temporal nature of real-world networks, the interest in community detection problems on dynamic networks have experienced an increasing attention over the last years. Genetic Algorithms, and other bio-inspired methods, have been successfully applied to tackle the community finding problem in static networks. However, few research works have been done related to the improvement of these algorithms for temporal or dynamic domains. This paper is focused on the design, implementation, and empirical analysis of a new Genetic Algorithm based on a hybrid-immigrants scheme, whose main goal is to improve the algorithm convergence when it is applied to identify communities on dynamic networks.