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Particle Swarm Optimization with Diverse Parameters

This paper proposes a particle swarm optimization (PSO) with diverse parameters that achieve an appropriate balance between diversification and intensification during the search based on numerical stability analysis. Numerical experiments using seven typical benchmark problems with 100, 500, and 1000 dimensions validate the robustness and search capabilities of the proposed PSO. © 2008 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.