Grey Wolf

The grey wolf optimizer (GWO) algorithm, inspired by grey wolf hunting behavior, is a prominent metaheuristic optimization technique currently employed across diverse scientific fields. Research focuses on enhancing GWO's performance through hybrid approaches, incorporating it into other algorithms (e.g., genetic algorithms, teaching-learning-based optimization) or modifying its core mechanisms to improve convergence speed and solution quality. These advancements are applied to various problems, including resource allocation, machine learning model training (e.g., neural networks, autoencoders), and feature selection, demonstrating GWO's versatility and potential for solving complex optimization challenges in diverse applications.