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arXiv · 2507.03022

A Novel Hybrid Grey Wolf Differential Evolution Algorithm

Ioannis D. Bougas·Pavlos Doanis·Maria S. Papadopoulou·Achilles D. Boursianis·Sotirios P. Sotiroudis·Zaharias D. Zaharis·George Koudouridis·Panagiotis Sarigiannidis·Mohammad Abdul Matint·George Karagiannidis·Sotirios K. Goudos
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Abstract

Grey wolf optimizer (GWO) is a nature-inspired stochastic meta-heuristic of the swarm intelligence field that mimics the hunting behavior of grey wolves. Differential evolution (DE) is a popular stochastic algorithm of the evolutionary computation field that is well suited for global optimization. In this part, we introduce a new algorithm based on the hybridization of GWO and two DE variants, namely the GWO-DE algorithm. We evaluate the new algorithm by applying various numerical benchmark functions. The numerical results of the comparative study are quite satisfactory in terms of performance and solution quality.

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Ioannis D. Bougas, Pavlos Doanis, Maria S. Papadopoulou, Achilles D. Boursianis, Sotirios P. Sotiroudis, Zaharias D. Zaharis, George Koudouridis, Panagiotis Sarigiannidis, Mohammad Abdul Matint, George Karagiannidis, Sotirios K. Goudos. 2025-07-02. A Novel Hybrid Grey Wolf Differential Evolution Algorithm. https://arxiv.org/abs/2507.03022

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