融合均匀变异与高斯变异的蝙蝠优化算法

被引：64

作者：

李煜 ^{[1
]}

裴宇航 ^{[2
]}

刘景森 ^{[3
]}

机构：

[1] 河南大学管理科学与工程研究所

[2] 河南大学计算机与信息工程学院

[3] 河南大学智能网络系统研究所

来源：

控制与决策 | 2017年 / 32卷 / 10期

关键词：

蝙蝠算法; 均匀变异; 高斯变异; 变异开关函数;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

140502 [人工智能];

摘要：

为提高蝙蝠算法的寻优精度和收敛速度,提出一种融合均匀变异和高斯变异的蝙蝠优化算法.算法引入变异开关函数,该函数使所有蝙蝠个体在任何时期都有概率发生变异,使种群保持较高的多样性和活跃性.同时在算法整个寻优过程中融入均匀变异和高斯变异,两种变异机制共同协作使算法首先快速定位到全局最优解区域,随后完成局部精确搜索.仿真结果表明,改进后的算法寻优性能显著提高,具有较快的收敛速度和较高的收敛精度.

引用

页码：1775 / 1781

页数：7

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