Metaheuristic Computation with MATLAB® by Erik Cuevas 9781000096538 100009653X

Metaheuristic Computation with MATLAB® Erik Cuevas – Ebook Instant Download/Delivery ISBN(s): 9780367438869,0367438860, 9781000096538, 100009653X

Product details:

• ISBN 10: 100009653X
• ISBN 13: 9781000096538
• Author: Erik Cuevas

Metaheuristic algorithms are considered as 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.　 Book Features: Provides a unified view of the most popular metaheuristic methods currently in use Includes the necessary concepts to enable readers to implement and modify already known metaheuristic methods to solve problems Covers design aspects and implementation in MATLAB® Contains numerous examples of problems and solutions that demonstrate the power of these methods of optimization The material has been written from a teaching perspective and, for this reason, this 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 from 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.

Table contents:

Chapter 2 ▪ Genetic Algorithms (GA)

Chapter 3 ▪ Evolutionary Strategies (ES)

Chapter 4 ▪ Moth–Flame Optimization (MFO) Algorithm

Chapter 5 ▪ Differential Evolution (DE)

Chapter 6 ▪ Particle Swarm Optimization (PSO) Algorithm

Chapter 7 ▪ Artificial Bee Colony (ABC) Algorithm

Chapter 8 ▪ Cuckoo Search (CS) Algorithm

Chapter 9 ▪ Metaheuristic Multimodal Optimization

Chapter 1 ▪ Introduction and Main Concepts

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