Grey Wolf Optimization Algorithm with Invasion-based Migration Operation

被引：0
|
作者：
Jitkongchuen, Duangjai [1 ]
Phaidang, Pongsak [1 ]
Pongtawevirat, Piyalak [1 ]
机构：
[1] Dhurakij Pundit Univ, Fac Informat Technol, Bangkok, Thailand
来源：
2016 IEEE/ACIS 15TH INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION SCIENCE (ICIS) | 2016年
关键词：
Metaheuristic algorithm; Grey wolf optimizer algorithm; Invasion-based migration;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposed a solution to improve the grey wolf optimizer performance with integrate the invasion-based migration operation. The traditional grey wolf optimizer algorithm have three main steps of hunting, searching for prey, encircling prey and attacking prey whereas the wolves have only one pack. The wolves in our proposed algorithm have more pack and have migrated between them. The invasion-based migration operation is used when the algorithm is trapped in the local optimum. The results are evaluated by a comparative with the traditional grey wolf optimizer (GWO) algorithm, particle swarm optimization (PSO) and differential evolution (DE) algorithm on 11 well-known benchmark functions. The experimental results showed that the proposed algorithm is capable of efficiently to solving complex optimization problems.
引用
收藏
页码：265 / 269
页数：5
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