Bald Eagle Search Algorithm: Optimization of McMurdo Antarctica Station and a literature Review, its Variants Applications

Bald Eagle Search Optimization for McMurdo Station explores the powerful Bald Eagle Search (BES) algorithm-a nature-inspired optimization technique modeled on the hunting behaviour of bald eagles-and its growing role in solving complex engineering and energy problems. The monograph explains BES theory, mathematical foundations, exploration-exploitation mechanisms and its three core phases, while tracing advances such as chaotic, opposition-based, Lévy-flight, adaptive, binary, multi-objective, hybrid, quantum-inspired and memetic variants. Its multidisciplinary applications span renewable energy, power systems, machine learning, smart grids, engineering, healthcare, communications and cybersecurity. At its centre is a compelling Antarctic case study: optimizing solar PV, wind and battery storage for McMurdo Station under extreme and isolated conditions. Comparisons with PSO, GA and ACO highlight BES's potential for reducing costs and emissions while improving reliability and renewable penetration. An essential resource for researchers, engineers and postgraduate students in intelligent optimization and sustainable energy.