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Particle swarm optimization (PSO) algorithm has shown fast and good search abilities in many unimodal and simple multimodal problems. However, PSO as well as other evolutionary algorithms (EAs) also suffers from the problem of premature convergence in solving some complex multimodal problems. The main reason is that the diversity of swarm decreases very quickly. In this paper, we propose a new PSO...
This paper presents a new diversity guided particle swarm optimization algorithm (PSO) named beta mutation PSO or BMPSO for solving global optimization problems. The BMPSO algorithm makes use of an evolutionary programming based mutation operator to maintain the level of diversity in the swarm population, thereby maintaining a good balance between the exploration and exploitation phenomena and preventing...
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