A Memetic Algorithm for Community Detection in Complex Networks
Résumé
Community detection is an important issue in the field of complex networks. Modularity is the most popular partition-based measure for community detection of networks represented as graphs. We present a hybrid algorithm mixing a dedicated crossover operator and a multi-level local optimization procedure. Experimental evaluations on a set of 11 well-known benchmark graphs show that the proposed algorithm attains easily all the current best solutions and even improves 6 of them in terms of maximum modularity.
Mots clés
algorithm analysis and problem complexity
Artificial Intelligence (incl. Robotics)
combinatorial optimization
community detection
complex networks
Computation by Abstract Devices
Computational Biology/Bioinformatics
Discrete Mathematics in Computer Science
graph partitioning
Heuristic
modularity
pattern recognition