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    付晓刚, 俞金寿. 基于混沌迁移策略的多种群差分进化算法[J]. 华东理工大学学报(自然科学版), 2009, (2): 308-312.
    引用本文: 付晓刚, 俞金寿. 基于混沌迁移策略的多种群差分进化算法[J]. 华东理工大学学报(自然科学版), 2009, (2): 308-312.
    Chaotic Migration Based Multi-population Differential Evolution Algorithm[J]. Journal of East China University of Science and Technology, 2009, (2): 308-312.
    Citation: Chaotic Migration Based Multi-population Differential Evolution Algorithm[J]. Journal of East China University of Science and Technology, 2009, (2): 308-312.

    基于混沌迁移策略的多种群差分进化算法

    Chaotic Migration Based Multi-population Differential Evolution Algorithm

    • 摘要: 针对差分进化算法全局寻优效率偏低的弱点,提出了一种基于多种群的混沌迁移策略,用以改进常规差分进化算法。该策略通过在多种群并行进化过程中引入混沌迁移序列,引导个体进行种群间的迁移。利用混沌的遍历性和随机性,保证子种群之间能够进行充分高效的信息交换。仿真实验和PID控制参数优化应用表明:该算法具有很强的全局搜索能力,寻优效率高,有效地克服了基本差分算法的早熟收敛问题。

       

      Abstract: To address the premature convergence in the searching process of differential evolution, a chaotic migration-based multi-population differential evolution (CMMPDE) is proposed. In this algorithm, the asynchronic migration of individuals during parallel evolution is guided by a chaotic migration sequence. Because the sequence is ergodic and stochastic , information exchanging among sub-populations is ensured to be efficient and sufficient . Simulation study of CMMPDE and its application of PID control parameters optimization have proved its capability of strong global search, superiority to SDE and high immunity against premature convergence.

       

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