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A Hybrid Global Optimization Algorithm Based on Wind Driven Optimization and Differential Evolution

机译：基于风动力优化和微分进化的混合全局优化算法

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摘要

This paper presents a new hybrid global optimization algorithm, which is based on the wind driven optimization (WDO) and differential evolution (DE), named WDO-DE algorithm. The WDO-DE algorithm is based on a double population evolution strategy, the individuals in a population evolved by wind driven optimization algorithm, and a population of individuals evolved from difference operation. The populations of individuals both in WDO and DE employ an information sharing mechanism to implement coevolution. This paper chose fifteen benchmark functions to have a test. The experimental results show that the proposed algorithm can be feasible in both low-dimensional and high-dimensional cases. Compared to GA-PSO, WDO, DE, PSO, and BA algorithm, the convergence speed and precision of WDO-DE are higher. This hybridization showed a better optimization performance and robustness and significantly improves the original WDO algorithm.
机译：本文提出了一种新的基于风驱动优化（WDO）和差分演化（DE）的混合全局优化算法，称为WDO-DE算法。 WDO-DE算法基于双重种群进化策略，种群中的个体通过风力驱动的优化算法进化，个体种群由差异运算演化而成。 WDO和DE中的个人人口都采用信息共享机制来实现协同进化。本文选择了十五种基准功能进行测试。实验结果表明，该算法在低维和高维情况下都是可行的。与GA-PSO，WDO，DE，PSO和BA算法相比，WDO-DE的收敛速度和精度更高。这种杂交显示了更好的优化性能和鲁棒性，并显着改进了原始WDO算法。

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  • 来源
    《Mathematical Problems in Engineering》 |2015年第22期|389630.1-389630.20|共20页
  • 作者

    Bao Zongfan; Zhou Yongquan; Li Liangliang; Ma Mingzhi;

  • 作者单位

    Guangxi Univ Nationalities, Coll Informat Sci & Engn, Nanning 530006, Guangxi, Peoples R China;

    Guangxi Univ Nationalities, Coll Informat Sci & Engn, Nanning 530006, Guangxi, Peoples R China|Key Lab Guangxi High Sch Complex Syst & Computat, Nanning 530006, Peoples R China;

    Guangxi Univ Nationalities, Coll Informat Sci & Engn, Nanning 530006, Guangxi, Peoples R China;

    Guangxi Univ Nationalities, Coll Informat Sci & Engn, Nanning 530006, Guangxi, Peoples R China;

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