Springer Handbook of Nature-Inspired Optimization Algorithms

Explore the current state of the art in computational intelligence with the Handbook of Nature-Inspired Optimization Algorithms. Published by Springer, this academic volume focuses on solving single objective bound-constrained real-parameter problems. It serves as a comprehensive resource for those studying complex systems, decision-making, and control processes. As part of the Systems, Decision and Control series, this book provides a deep look into the methodologies used to address modern optimization challenges. Whether you are a researcher, student, or professional in the field of computer science, this text offers the technical foundation needed to understand how nature-inspired methods can be applied to real-world mathematical problems. This volume is designed to support advanced learning and research in AI and machine learning applications.