PROJECT TITLE :
A Multiobjective Genetic Algorithm to Find Communities in Complex Networks
A multiobjective genetic algorithm to uncover community structure in advanced network is proposed. The algorithm optimizes 2 objective functions in a position to identify densely connected groups of nodes having sparse inter-connections. The strategy generates a group of network divisions at different hierarchical levels in which solutions at deeper levels, consisting of a better number of modules, are contained in solutions having a lower range of communities. The number of modules is automatically determined by the better tradeoff values of the target functions. Experiments on artificial and real life networks show that the algorithm successfully detects the network structure and it's competitive with state-of-the-art approaches.
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