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Multi-population Coevolutionary Differential Evolution Algorithm

机译:多人共同差分差分算法

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The multi-population coevolutionary differential evolution (DE) based on estimation of distribution algorithm (EDA) is proposed. DE completes optimum search using the difference information between the individuals in the population, but the global population evolution information can not be used sufficiently. In this paper, the multi-population co-evolutionary is introduced, which incorporate the merits of the DE and EDA. The elite mutation is proposed in DE. To overcome the greed characteristic, the chaotic initialization and replacement are introduced in DE and the individual diversity in EDA is adjusted based on the individual density. Simulation results show the good global search ability of the proposed algorithm.
机译:提出了基于分布算法(EDA)估计的多群合格差分进化(DE)。 DE完成使用人口中个人之间的差异信息的最佳搜索,但无法充分使用全球人口演化信息。在本文中,介绍了多人共进进化,其中包括DE和EDA的优点。 Elite突变在de中提出。为了克服贪婪特征,在DE中引入混沌初始化和替代,并且基于个体密度调整EDA中的个体多样性。仿真结果显示了所提出的算法的良好全球搜索能力。

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