Abstract:Particle Swarm Optimization (PSO) is a swarm intelligence-based metaheuristic algorithm inspired by the foraging behaviors of fish or birds. Despite the advantages of having a simple and effective working structure, PSO also has some disadvantages, such as early convergence, getting trapped in local minima, and weak global search capabilities. In this study, a novel intensification strategy based on K-Means clustering has been proposed to enhance the performance of PSO. The proposed method is called Particle S… Show more
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