Metaheuristic Computation with MATLAB®

Metaheuristic algorithms are considered generic optimization tools that can solve very complex problems characterized by having very large search spaces. Metaheuristic methods reduce the effective size of the search space through the use of effective search strategies.&nbsp; Book Features: ·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Provides a unified view of the most popular metaheuristic methods currently in use ·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Includes the necessary concepts to enable readers to implement and modify already known metaheuristic methods to solve problems ·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Covers design aspects, but also implementation in MATLAB ·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Contains numerous examples of problems and solutions that demonstrate the power of these methods of optimization &nbsp; The material has been written from a teaching perspective and for this reason, the book is primarily intended for undergraduate and postgraduate students of Artificial Intelligence, Metaheuristic methods and/or Evolutionary Computation. The objective is to bridge the gap between metaheuristic techniques and complex optimization problems that profit on the convenient properties of metaheuristic approaches. Therefore, engineer practitioners, who are not familiar with metaheuristic computation, will appreciate that the techniques discussed are beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise in such areas.

Computers & Technology

Rodríguez, Alma

Cuevas, Erik

Computer Science

Chapman and Hall/CRC

Image Processing and Machine Learning, Volume 1

Rodríguez, Alma Nayeli

Image Processing and Machine Learning, Volume 2

Machine Learning and Metaheuristic Computation

Gálvez, Jorge

Avalos, Omar

Wario, Fernando

Wiley-IEEE Press

This book presents new, alternative metaheuristic developments that have proved to be effective in various complex problems to help researchers, lecturers, engineers, and practitioners solve their own optimization problems. It also bridges the gap between recent metaheuristic techniques and interesting identification system methods that benefit from the convenience of metaheuristic schemes by explaining basic ideas of the proposed applications in ways that can be understood by readers new to these fields. As such it is a valuable resource for energy practitioners who are not researchers in metaheuristics. In addition, it offers members of the metaheuristic community insights into how system identification and energy problems can be translated into optimization tasks.

Recent Metaheuristics Algorithms for Parameter Identification (Studies in Computational Intelligence, 854)

Springer

Recent Metaheuristics Algorithms for Parameter Identification (Studies in Computational Intelligence)

This book includes two objectives. The first goal is to present advances and developments which have proved to be effective in their application to several complex problems. The second objective is to present the performance comparison of various metaheuristic techniques when they face complex optimization problems. The material has been compiled from a teaching perspective. Most of the problems in science, engineering, economics, and other areas can be translated as an optimization or a search problem. According to their characteristics, some problems can be simple that can be solved by traditional optimization methods based on mathematical analysis. However, most of the problems of practical importance in engineering represent complex scenarios so that they are very hard to be solved by using traditional approaches. Under such circumstances, metaheuristic has emerged as the best alternative to solve this kind of complex formulations. This book is primarily intended for undergraduate and postgraduate students. Engineers and application developers can also benefit from the book contents since it has been structured so that each chapter can be read independently from the others, and therefore, only potential interesting information can be quickly available for solving an industrial problem at hand.&nbsp; &nbsp;

Recent Metaheuristic Computation Schemes in Engineering (Studies in Computational Intelligence, 948)

Alejo-Reyes, Avelina

Del-Valle-Soto, Carolina

Reference

Analysis and Comparison of Metaheuristics (Studies in Computational Intelligence, 1063)

This textbook provides readers a comprehensive introduction to numerical methods, using MATLAB®. The authors discuss the theory and application of the most often used numerical methods, using MATLAB as a computational tool. The book is designed to be accessible to readers of varying backgrounds, so the presentation focuses more on the description, implementation, and application of the methods and less on the mathematical details. This book not only covers the most important methods and techniques of scientific computation, but also contains a great amount of code and implementations, facilitating the process of learning and application.

Computational Methods with MATLAB® (Synthesis Lectures on Engineering, Science, and Technology)

Luque, Alberto

Escobar, Héctor

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