Computational Intelligence-based Optimization Algorithms: From Theory to Practice

Computational intelligence-based optimization methods, or metaheuristic optimization algorithms, are a popular topic in mathematical programming. This book covers selected effective and renowned algorithms, providing practical insights and theoretical ideas. Each chapter includes Python code for implementation, making it a valuable resource for beginners and intermediate programmers.

Format: Hardback
Length: 338 pages
Publication date: 11 October 2023
Publisher: Taylor & Francis Ltd

Computational intelligence-based optimization methods, also referred to as metaheuristic optimization algorithms, have gained significant attention in the field of mathematical programming. These methods have played a pivotal role in bridging the gap between different approaches and emerging as a powerful tool for solving real-world optimization problems. In this comprehensive book, we have curated a selection of the most effective and renowned algorithms in the literature. Not only are these algorithms practical and applicable in various domains, but they also offer insightful theoretical concepts that aid in understanding their underlying mechanisms. Each chapter provides a brief overview of the algorithm's background and the fields in which it has been successfully employed. Furthermore, comprehensive Python code is provided at the end of each chapter, making this book an invaluable resource for both beginner and intermediate programmers seeking to delve into these algorithms. By exploring the intricacies of these algorithms, readers will gain a deeper understanding of their capabilities and how they can be applied to address complex optimization challenges. Whether you are a researcher, engineer, or practitioner looking to enhance your optimization skills, this book is a must-have for your library.

Weight: 816g
Dimension: 234 x 156 (mm)
ISBN-13: 9781032544168