Whale optimization algorithm: analysis and full survey

The whale optimization algorithm (WOA) is a metaheuristic algorithm inspired by the hunting behavior of humpback whales. This paper presents a comprehensive analysis and survey of the WOA, examining its key components, variations, and applications. The algorithm's encircling prey, bubble-net feeding, and search for prey steps are explained in detail, highlighting their role in balancing exploration and exploitation. Various adaptations and hybridizations of the WOA are reviewed, including adaptive strategies, constrained and multiobjective optimization extensions, and combinations with other algorithms. The survey further discusses the algorithm's performance on a wide range of optimization problems, showcasing its competitiveness and effectiveness. Finally, the paper concludes with insights into the strengths, limitations, and potential future directions of the WOA. This analysis and survey aim to provide researchers and practitioners with a comprehensive understanding of the WOA and its applications, fostering further advancements in the field of nature-inspired optimization algorithms.