1st Edition
Metaheuristic Computation with MATLAB®
280 Pages
100 B/W Illustrations
by
Chapman & Hall
280 Pages
100 B/W Illustrations
by
Chapman & Hall
280 Pages
100 B/W Illustrations
by
Chapman & Hall
Also available as eBook on:
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... Read more
Preface. Acknowledgments. Authors. Chapter 1 Introduction and Main Concepts. 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. Index.
Biography
Erik Cuevas is a professor in the Department of Electronics at the University of Guadalajara, Mexico.
Alma Rodríguez is a PhD candidate in electronics and computer science at the University of Guadalajara, Mexico.
