Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems: 1038 (Studies in Computational Intelligence, 1038) - Softcover

Softcover

ISBN 10: 3030990818 ISBN 13: 9783030990817

Publisher: Springer, 2026

Synopsis

This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems. This book has exciting chapters that employ evolutionary and swarm optimization tools combined with machine learning techniques. The fields of applications are from distribution systems until medical diagnosis, and they are also included different surveys and literature reviews that will enrich the reader. Besides, cutting-edge methods such as neuroevolutionary and IoT implementations are presented in some chapters. In this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. 

The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and can be used in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the material canbe helpful for research from the evolutionary computation, artificial intelligence communities.

 

About this title

From the Back Cover

This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems. This book has exciting chapters that employ evolutionary and swarm optimization tools combined with machine learning techniques. The fields of applications are from distribution systems until medical diagnosis, and they are also included different surveys and literature reviews that will enrich the reader. Besides, cutting-edge methods such as neuroevolutionary and IoT implementations are presented in some chapters. In this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms.

The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and can be used in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the material can be helpful for research from the evolutionary computation, artificial intelligence communities.

Edition details

• Publisher: Springer
• Publication date: 2026
• Language: English
• ISBN 10: 3030990818
• ISBN 13: 9783030990817
• Binding: Paperback
• Edition number: 1
• Number of pages: 506
• Editor: Houssein Essam Halim, Abd Elaziz Mohamed, Oliva Diego, Abualigah Laith