Hybrid Krill Herd Algorithm with Vortex Search for Global Numerical Optimization

被引：2
|
作者：
YANG Jian [1 ]
WAN Zhongping [1 ]
PENG Zhenhua [1 ]
机构：
[1] School of Mathematics and Statistics, Wuhan University
来源：
Wuhan University Journal of Natural Sciences | 2020年 / 25卷 / 02期
基金：
中国国家自然科学基金;
关键词：
krill herd algorithm; global optimization problem; hybrid vortex search operator(HVS);
D O I：
10.19823/j.cnki.1007-1202.2020.0012
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In order to solve the problem that the krill herd(KH) algorithm is premature due to the decrease of population diversity, a new hybrid vortex search KH(VSKH) algorithm has been developed to deal with the global optimization problem. The improvement is that a new hybrid vortex search(HVS) operator is added into the updating process of the krill for the purpose of dealing with optimization problems more efficiently. Using 20 benchmark functions for comparison experiments, the results show that the VSKH algorithm has higher accuracy.
引用
收藏
页码：109 / 117
页数：9
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