Intelligent Evolutionary Optimization 1st Edition

Unlock the next generation of problem-solving with Intelligent Evolutionary Optimization, 1st Edition by Hua Xu and Yuan Yuan. This authoritative guide brings together rigorous theory and practical insight to help researchers, engineers, and advanced students master evolutionary algorithms and intelligent optimization methods.

Inside, readers will find clear explanations of foundational principles, state-of-the-art metaheuristics, and modern hybrid approaches that blend machine learning with evolutionary search. The authors walk through algorithm design, multi-objective optimization, constraint handling, convergence analysis, and performance benchmarking—each topic presented with clarity and real-world examples that illustrate how techniques translate into measurable improvements.

Whether you work in engineering design, logistics and scheduling, energy systems, or data-driven product development, this volume equips you with strategies to tackle complex, high-dimensional problems. Emphasis on practical applicability and transferable methodology means the book is globally relevant—from academic labs and R&D teams to industry practitioners in North America, Europe, and Asia.

Concise, well-structured chapters and illustrative case studies make complex concepts accessible without sacrificing depth. With contributions from leading experts and a focus on contemporary challenges, Intelligent Evolutionary Optimization is the go-to resource for anyone aiming to push optimization performance and innovation forward.

Add this essential reference to your professional library today and start transforming optimization challenges into competitive advantages.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.