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Dergiler / Gazi University Journal of Science / 2026 / Volume: 35 Issue: 2

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

Emmanuel Dada(University of Maiduguri)0000-0002-1132-5447
Stephen Joseph(University of Maiduguri, Maiduguri, Nigeria)0000-0001-5701-2633
David Oyewola(Federal University Kashere, Gombe, Nigeria)0000-0001-9638-8764
Alaba Ayotunde Fadele(Federal College of Education, Zaria)0000-0002-1125-0780
Haruna Chiroma(National Yunlin University of Science and Technology, Doulin, Taiwan)0000-0003-3446-4316
Shafi'i Muhammad Abdulhamid(Federal University of Technology Minna, Minna, Nigeria)0000-0001-9196-9447
Sayfa
—
Yayın Tarihi
2022-06-01
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

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 Maddede Bu Makale

🎯
Amaç & Hipotez:The development of Grey Wolf Optimisation (GWO) Algorithm was motivated by the biological behaviours of swarm of wolves hunting for prey.
📊
Temel Bulgular & Veri:Suggestions for new research directions that have the capacity to increase the performance of GWO are presented.
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Sonuç & Katkı: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.
🔬Tür:Literatür & Derleme Çalışması
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler: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.

🔖

Bu Makaleye Atıf Yap

Dada, E., Joseph, S., Oyewola, D., 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, Volume: 35 Issue: 2. https://doi.org/10.35378/gujs.820885

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