Title: Particle Swarm Optimization Algorithm Based on Individual State
Abstract: Concerning the fact that the standard Particle Swarm Optimization(PSO) algorithm has the problem of population diversity lose and premature convergence,using the feature of independent individual behavior of social animals in nature for reference,this paper proposes the concept of individual state.A Particle Swarm Optimization(PSO) algorithm based on individual state and state transition is proposed and tested with several typical benchmark functions.The result indicates that the algorithm is significantly superior to standard PSO in performance of optimization.Compared with other improved algorithms,it is also excellent in performance of optimization.
Publication Year: 2011
Publication Date: 2011-01-01
Language: en
Type: article
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