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A hybrid strategy combining differential evolution with simplex gradient

机译:结合差分进化与单纯形梯度的混合策略

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Differential Evolution has been made great achievements in various fields such as computational sciences, engineering optimization, and operations management. However, the choice of the mutation strategy is important to the performance of DE. In order to enhance the performance of DE, we present a hybrid strategy combining differential evolution with simplex gradient. The hybrid strategy can maintain the appropriate balance between exploration and exploitation. The comparisons of numerical experiments among the proposed algorithm with the hybrid strategy and four other algorithms with the different setting strategies are done, which show that the proposed algorithm outperforms the other compared algorithms.
机译:差异进化在计算科学,工程优化和运营管理等各个领域都取得了巨大成就。但是,突变策略的选择对DE的性能很重要。为了提高DE的性能,我们提出了一种混合策略,将差分进化与单纯形梯度相结合。混合策略可以在勘探和开发之间保持适当的平衡。将该算法与混合策略和其他四种设置策略不同的算法进行了数值实验比较,结果表明该算法优于其他算法。

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