A multiobjective genetic algorithm to uncover community structure in complex network is proposed. The algorithm optimizes two objective functions able to identify densely connected groups of nodes having sparse interconnections. The method generates a set of network divisions at different hierarchical levels in which solutions at deeper levels, consisting of a higher number of modules, are contained in solutions having a lower number of communities. The number of modules is automatically determined by the better tradeoff values of the objective functions. Experiments on synthetic and real life networks show the capability of the method to successfully detect the network structure.
['Clara Pizzuti']
A Multi-objective Genetic Algorithm for Community Detection in Networks