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Particle swarm optimization has been successfully applied in many research and application areas because of its effectiveness and easy implementation. In this work we extend one of its variants to address multi-modal dynamic optimization problems, the multi-swarm PSO (mPSO) proposed by Blackwell and Branke. The aim of our proposal is to increase the efficiency of this algorithm. To this end, we propose techniques operating at swarm level: one of which divides each swarm into two groups depending on the quality of the particles for facing the loss of diversity, and the other control the number of active swarms during the run using a fuzzy rule. A detailed experimental analysis shows the robustness of our proposal.

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