Application of Grey Wolf Optimization Algorithm: Recent Trends, Issues, and Possible Horizons

Year 2022, , 485 - 504, 01.06.2022

Emmanuel Dada , Stephen Joseph , David Oyewola , Alaba Ayotunde Fadele , Haruna Chiroma , Shafi'i Muhammad Abdulhamid

https://doi.org/10.35378/gujs.820885

Cited By: 18

Abstract

The development of Grey Wolf Optimisation (GWO) Algorithm was motivated by the biological behaviours of swarm of wolves hunting for prey. This paper presents recent progress on Grey Wolf Optimization (GWO) algorithm, its variants and their applications, issues, and likely prospects. The review revealed that opportunities still exists for development of more robust and stable variants of GWO that will overcome the shortcomings of existing variants. This review has the potential to stimulate researchers in the area of nature-inspired algorithms to further advance the effectiveness of the GWO and its ability to solve problems. Such problems can be real-life, complicated and nonlinear optimization problems in different domain of human endeavour. Suggestions for new research directions that have the capacity to increase the performance of GWO are presented. It is expected that this paper will serve as reading material for beginners whereas experienced researchers can also use it as an article yardstick for further development of GWO algorithms. 

Keywords

Grey wolf optimisation, Single objective gwo, Multi-objective gwo, Hybrid gwo

Supporting Institution

None

Project Number

None

Thanks

This research work has no funding.

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