An Improved Firefly Algorithm Based on An Attraction Switch

被引：0
|
作者：
Liu, Jianxun [1 ]
Shi, Jinfei [1 ,2 ]
Hao, Fei [2 ]
机构：
[1] Southeast Univ, Sch Mech Engn, Nanjing 211189, Peoples R China
[2] Nanjing Inst Technol, Sch Mech Engn, Nanjing 211167, Peoples R China
来源：
2021 INTERNATIONAL SYMPOSIUM ON COMPUTER SCIENCE AND INTELLIGENT CONTROLS (ISCSIC 2021) | 2021年
基金：
中国国家自然科学基金;
关键词：
FA; attraction switch; convergence behavior; continuous optimization; AS-IFA;
D O I：
10.1109/ISCSIC54682.2021.00070
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Firefly algorithm(FA) is a new swarm intelligence optimization algorithm.For any two firefly individuals that are far apart,the attraction module of the FA at this moment loses its attraction during each iteration.This is a poor convergence of the FA,and it is easy to fall into a local optimum. In order to overcome the shortcoming,based on the standard firefly algorithm and LF-FA,the paper proposes a improved firefly algorithm(AS-IFA) that switches attractive modules.The AS-IFA has a strong attraction for any firefly that is far away.At the same time, it also has obvious attraction to the closer fireflies.The experimental results show that compared with the standard firefly algorithm and its variant algorithm,the AS-IFA has the best convergence behavior,and its global exploration efficiency is the best.
引用
收藏
页码：355 / 360
页数：6
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