Springer Multi-objective Optimization Techniques in Engineering Applications: Advanced Methods for Solving Complex Engineering Problems: 1184 (Studies in Computational Intelligence, 1184)

This essential book bridges theory and practice, exploring advanced multi-objective optimization methods applied across engineering fields like manufacturing, renewable energy, and thermal management. This book presents a comprehensive, hands-on guide for engineers, researchers, and students seeking to harness the power of optimization in diverse, real-world scenarios. Through expertly crafted chapters, this book illuminates the strengths of state-of-the-art metaheuristic algorithms―such as the Harris hawk optimization, whale optimization, gray wolf optimization, sunflower optimization, imperialistic competitive optimization, jaya optimization, thermal exchange optimization, grasshopper optimization, and cuckoo search optimization. These algorithms tackle complex, high-dimensional challenges, giving readers invaluable tools to boost performance and efficiency. Case studies breathe life into these methods, showcasing their adaptability in systems with multiple conflicting objectives. Readers will find practical MATLAB and GAMS models, enabling immediate experimentation and application. In an era where efficiency and sustainability are paramount, this book equips engineers to solve today’s toughest optimization problems, making it an indispensable resource for those committed to innovation. Whether focused on energy systems, structural design, or computational mechanics, this book serves as a trusted guide to achieving breakthrough solutions across multiple disciplines.