Improved Artificial Bee Colony Algorithm Guided by Experience

被引：0

作者：

Wang, Chunfeng ^{[1
,2
]}

Shang, Pengpeng ^{[3
]}

Liu, Lixia ^{[4
]}

机构：

[1] Xianyang Normal Univ, Sch Math & Stat, Xianxiang 712000, Peoples R China

[2] Henan Normal Univ, Coll Math & Informat, Xinxiang 453007, Henan, Peoples R China

[3] Henan Normal Univ, Coll Math & Informat Sci, Xinxiang 453007, Henan, Peoples R China

[4] Xidian Univ, Sch Math & Stat, Xian 710126, Peoples R China

来源：

ENGINEERING LETTERS | 2022年 / 30卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Artificial bee colony; Optimization; Swarm intelligence; Direction information; OPTIMIZATION;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

At present, artificial bee colony algorithm (ABC) is one of the hot issues in swarm intelligence algorithm. Since it was proposed, people have done a lot of improvement work for ABC algorithm. To address the shortcomings of ABC, an improved ABC guided by experience (named as EABC) is proposed in this paper. In EABC, it collects the experience of individual improvement caused by dimension change in the iterative process, and selects the dimensions to change according to a ratio when a new position needs to be generated. In this way, the individual can choose a good direction to improve its quality. Numerical experiments show that EABC has a better performance.

引用

页码：261 / 265

页数：5

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