杜艳艳, 刘升. 带有高斯变异的Lévy飞行改进蝙蝠算法[J]. 微电子学与计算机, 2018, 35(3): 83-87, 92.
引用本文: 杜艳艳, 刘升. 带有高斯变异的Lévy飞行改进蝙蝠算法[J]. 微电子学与计算机, 2018, 35(3): 83-87, 92.
DU Yan-yan, LIU Sheng. An Improved Bat Algorithm With Gauss Mutation and Lévy Flights[J]. Microelectronics & Computer, 2018, 35(3): 83-87, 92.
Citation: DU Yan-yan, LIU Sheng. An Improved Bat Algorithm With Gauss Mutation and Lévy Flights[J]. Microelectronics & Computer, 2018, 35(3): 83-87, 92.

带有高斯变异的Lévy飞行改进蝙蝠算法

An Improved Bat Algorithm With Gauss Mutation and Lévy Flights

  • 摘要: 提出一种带有高斯变异的Lévy飞行特征的改进蝙蝠算法(GMBA).该算法中, 每只蝙蝠根据当前位置的优劣程度选择不同的飞行方式, 位置较差的采用Lévy飞行, 位置较好的逐步向群体最优位置移动; 最后在算法满足变异条件时, 应用高斯变异策略, 从而在一定程度上避免了算法陷入局部最优, 并能获得高精度的解.结果显示, GMBA的优化性能有了显著的提高.

     

    Abstract: An improved bat algorithm with Gauss mutation and Lévy Flights (GMBA) is proposed in this paper, in which each bat chooses different flight strategy according to its state at present. Bat in worse position choose to Lévy flight behaviors.Bat in better solution move to best solution. Moreover, when meeting the condition of the variation, The GMBA performed the Gauss mutation operation to improve the ability of the bat trapping out of the local optima. Fourteen typical experiments show that the new algorithm (GMBA) is superior than BA and LBA.

     

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