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Journals / Gazi University Journal of Science / 2022 / Cilt: 35 - Sayı: 2

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

Emmanuel Gbenga DADA
Stephen Bassi JOSEPH
David Opeoluwa OYEWOLA
Alaba Ayotunde FADELE
Haruna CHIROMA
Shafi'i Muhammad ABDULHAMID
Pages
485–504
Publication Date
2022-11-08
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

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.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The development of Grey Wolf Optimisation (GWO) Algorithm was motivated by the biological behaviours of swarm of wolves hunting for prey.
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Key Findings & Data:Suggestions for new research directions that have the capacity to increase the performance of GWO are presented.
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Conclusion & Impact: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.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:Grey wolf optimisation · Single objective gwo · Multi-objective gwo

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.

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Cite This Article

DADA, E. G., JOSEPH, S. B., OYEWOLA, D. O., FADELE, A. A., CHIROMA, H., ABDULHAMID, S. M. (2022). Application of Grey Wolf Optimization Algorithm: Recent Trends, Issues, and Possible Horizons. Gazi University Journal of Science, Cilt: 35 - Sayı: 2, 485–504. https://ajindex.com/articles/649102

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