Metaheuristic Computation with MATLAB (R)

Metaheuristic algorithms are generic optimization tools that can solve complex problems with large search spaces by reducing the effective size of the search space through effective search strategies. This book provides a unified view of popular metaheuristic methods, concepts, and implementation in MATLAB, with examples and problems to demonstrate their power. It is primarily intended for undergraduate and postgraduate students of artificial intelligence, metaheuristic methods, and evolutionary computation, bridging the gap between metaheuristic techniques and complex optimization problems.

Format: Paperback / softback
Length: 280 pages
Publication date: 06 May 2022
Publisher: Taylor & Francis Ltd

Metaheuristic algorithms are highly regarded as versatile optimization tools capable of tackling exceedingly complex problems characterized by vast search spaces. These methods employ efficient search strategies to significantly narrow down the dimensions of the search space, thereby enhancing the effectiveness of the optimization process.

This comprehensive book offers a unified perspective on the most widely employed metaheuristic methods currently in use. It provides the essential concepts and insights necessary for readers to implement and modify existing metaheuristic methods to solve diverse problems. Furthermore, it delves into design aspects and practical implementation using the MATLAB® platform. Numerous examples of problems and their corresponding solutions are included, showcasing the remarkable power and effectiveness of these optimization techniques.

The book has been meticulously crafted with a teaching orientation, making it primarily designed for undergraduate and postgraduate students specializing in artificial intelligence, metaheuristic methods, and/or evolutionary computation. Its primary objective is to bridge the gap between metaheuristic techniques and complex optimization problems that greatly benefit from the inherent advantages offered by metaheuristic approaches. Consequently, engineer practitioners who may not have prior experience with metaheuristic computation will find value in the techniques discussed, as they have been adapted and refined to address significant challenges commonly encountered in fields such as engineering, science, and business.

By presenting the material in a clear and concise manner, this book serves as a valuable resource for students seeking to gain a deeper understanding of metaheuristic algorithms and their applications in solving complex optimization problems. It equips them with the knowledge and skills necessary to apply these techniques effectively, enabling them to contribute to the field of optimization and make meaningful contributions to real-world applications.

Weight: 517g
Dimension: 254 x 178 (mm)
ISBN-13: 9780367523800