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• W2361363212 abstract "To the problems of premature convergence frequently appeared in standard particle swarm optimization(PSO) algorithm and its poor convergence,a particle swarm optimization algorithm with the search operator of artificial bee colony is proposed.Firstly,the method makes full use of the exploration of artificial bee colony algorithm search operator to help the algorithm to jump out of the likely local optima.Then to enhance the global convergence,when producing the initial population,both chaotic maps and opposition-based learning based method is proposed.Moreover,simulation experiment on a suite of 12 benchmark functions is given,and the comparisons with other algorithms are provided.The results show that the proposed approach has better convergence rate and great capability of preventing premature convergence." @default.
• W2361363212 created "2016-06-24" @default.
• W2361363212 creator A5018252935 @default.
• W2361363212 date "2012-01-01" @default.
• W2361363212 modified "2023-09-26" @default.
• W2361363212 title "Particle swarm optimization with search operator of artificial bee colony algorithm" @default.
• W2361363212 hasPublicationYear "2012" @default.
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