a multi-objective community detection method based on swarm intelligence

What is it about?

Community detection is one of the major challenges in analyzing social networks.Therefore, we proposed a multi-objective optimization method which utilizes the benefits of evolutionary algorithms such as strength and flexibility on the one hand and convergence speed along with the high performance of particle swarm optimization method on the other hand.

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Why is it important?

First of all, particles are initialized by applying an initialization method based on an opposition-learning strategy. Then, the particles move toward the search space to find the optimal solution, and update their current states by updating the position and the velocity of particles. Also, in order to maintain the diversity of the population, and escape from the local optima, a mutation operator was applied. The accuracy of the partition was evaluated by the most common multi-objective function.