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- W33509296 abstract "Efficiency of the evolutionary algorithms (EAs) is strongly dependent on the parameter setting. Differential evolution (DE) is well known as a simple and efficient evolutionary algorithm over continuous spaces. Of the three main parameters which control DE's behavior-population size NP, scaling factor F and crossover rate CR-CR is the most important. Despite the important role CR plays in effecting the performance of DE there are few studies that have examined the adaptive or self-adaptive strategies of CR. This paper is aim to investigate the influence of CR on the behavior of DE both from a theoretical and numerical point of view. In addition, a novel self-adaptive scheme for the evolution of CR based on a cloud model is proposed to enhance the convergence performance of DE. Experimental results confirm the superiority of the new scheme over several state-of-the-art self-adaptive DE versions." @default.
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- W33509296 date "2012-05-18" @default.
- W33509296 modified "2023-09-27" @default.
- W33509296 title "Differential Evolution with Cloud Model Based Self-adaptive Crossover Strategy" @default.
- W33509296 doi "https://doi.org/10.1109/icetce.2012.230" @default.
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