The book includes both basic concepts and sophisticated hybrid architectures that interface with modern technologies like blockchain and artificial intelligence, connecting theoretical underpinnings with real-world applications. Because of this strategy, students, researchers, and business professionals who want to comprehend and use evolutionary computation techniques will find the material to be equally beneficial. The varied case studies and different viewpoints give readers a worldwide perspective on adaptive problem-solving techniques. This book shows how genetic algorithms continue to develop as potent methods for tackling challenging real-world problems in a variety of scientific and technical fields, acting as both a reference and a useful manual.

Nilanjan Dey is a Professor in the Department of Computer Science and Engineering at Techno International New Town, Kolkata, India. He received his B.Tech. and M.Tech. degrees in Information Technology and his Ph.D. in Electronics and Telecommunication Engineering. His research interests span nature‑inspired computing, evolutionary algorithms, ambient intelligence, and data‑intensive systems. He serves as Editor‑in‑Chief of the International Journal of Ambient Computing and Intelligence and as Associate Editor of IEEE Transactions on Technology and Society. He is also Series Co‑Editor of Springer Tracts in Nature‑Inspired Computing and Data‑Intensive Research and Advances in Ubiquitous Sensing Applications for Healthcare (Elsevier), and sits on the Editorial Board of IEEE Data Descriptions. A Visiting Fellow at the University of Reading (UK), he is a Fellow of IETE and a Senior Member of IEEE.