Metaheuristic optimization has become a prime alternative for solving complex optimization problems in several areas. Hence, practitioners and researchers have been paying extensive attention to those metaheuristic algorithms that are mainly based on natural phenomena. However, when those algorithms are implemented, there are not enough books that deal with theoretical and experimental problems in a friendly manner so this book presents a novel structure that includes a complete description of the most important metaheuristic optimization algorithms as well as a new proposal of a new metaheuristic optimization named earthquake optimization. This book also has several practical exercises and a toolbox for MATLAB® and a toolkit for LabVIEW are integrated as complementary material for this book. These toolkits allow readers to move from a simulation environment to an experimentation one very fast. This book is suitable for researchers, students, and professionals in several areas, such as economics, architecture, computer science, electrical engineering, and control systems.
The unique features of this book are as follows:
The authors are multidisciplinary/interdisciplinary lecturers and researchers who have written a structure-friendly learning methodology to understand each metaheuristic optimization algorithm presented in this book.
Dr. Pedro Ponce is a Senior Researcher Scientist and member of the Product In- novation Research Group at Teccnologico de Monterrey in Mexico City. He received the B.Eng. degree in Automation and Control, the M.Sc. and Ph.D. degree in Electri- cal Engineering focused on Automatic Control Systems, respectively. He worked for more than 12 years as a field and design engineer in Control Systems and Automation. Also, He has authored and co-authored more than 100 research articles, 14 books, and 6 inventions, including one US Patent. His research interests include Mechatronics, Control Systems, Smart Grids, Machine Learning, Product Design, Optimization, Electric Engineering, Education and Artificial Intelligence. He is a member of the Mexican National Researchers System, and Mexican Academy of science. Besides, He is an associate editor in the international journal of advanced robotics systems and the international journal on interactive design and manufacturing.
Dr. Arturo Molina is Vice President of Research and Technology Transfer and Pro- fessor from Tecnologico de Monterrey University in Mexico. He received the B.Eng. degree in computational systems and the M.Eng. degree in computational sciences from the Tecnologico de Monterrey and his PhD degree in Manufacturing Engineer- ing at Loughborough University of Technology and his University Doctor degree in Mechanical Engineering at the Technical University of Budapest, Hungary. He has co-authored more than 300 research articles and several inventions. His current research interests include concurrent engineering technologies and manufacturing, enterprise integration engineering, technology management he has applied research and development for the economic sectors of automotive, construction and energy. He is a member of the Mexican National Researchers System, the Mexican Academy of Science and the Mexican Academy of Engineering.
Dr. Ricardo A. Ramírez-Mendoza received a Ph.D. degree from INPG, France in1997. He is now Professor of Mechatronics and Mechanics Engineering and Dean of Research, National School of Engineering and Science at the Tecnologico de Mon- terrey within School of Engineering and Science. His main research interests include applications of advanced control to automotive systems, fault detection and isola- tion (FDI), electromobility, biomedical signal processing and engineering education. He is the (co-)author of 3 books, more than 100 papers in top journals and more than 170 international conference papers and more than 1,000 citations. Besides, he has worked as expert consulting for different industries and regional development project.
Efraín Méndez received the B.S. degree in Mechatronics Engineering from the Tecnologico de Monterrey, Mexico City Campus, Mexico. After the B.S. degree, he was in charge of electronics software and hardware design between 2016 and 2019, as part of a startup team dedicated to the design of power inverters for the control of three-phase induction motors. As part of the Project 266632 "Laboratorio Binacional para la Gestión Inteligente de la Sustentabilidad Energíetica y la Formación Tecnologica" ("Bi-National Labora- tory on Smart Sustainable Energy Management and Technology Training"), funded by the CONACYT (Consejo Nacional de Ciencia y Tecnología) SENER (Secretaría de Energía) Fund for Energy Sustainability (Agreement S0019201401), Efraín joined in 2016 the Ph.D. in engineering sciences program in the Tecnologico de Monterrey, where he is currently involved in PV and Power electronics research topics, specially dealing with the development of MPPT through metaheuristic algorithms.
Msc. Alexandro Ortiz is PhD candidate from Tecnologico de Monterrey in power electronics, energy harvesting, and renewable energy. Alexandro has a Bs. and MsC. in automatic control. He has currently 3 years of teaching experience and 5 years of industrial experience.
Dr. David Balderas was Born in Mexico City, Mexico. He received the B.Eng. in mechatronics engineering from Universidad Panamericana in 2005, his M.S. in biomedical engineering from Delft University of Technology in 2009, and the Ph.D. degree in engineering sciences, with specialization on Artificial Intelligence and Brain- Computer Interfaces from Tecnologico de Monterrey CCM in 2018. Since 2014, he has been an Assistant Professor and Researcher at Tecnologico de Monterrey teaching more than 10 different subjects. He is author of 2 book chapters and 8 research articles. His research interests include artificial intelligence especially neural networks, classification, optimization, parameter estimation, reinforcement learning; and biomedical applications such as brain computer interfaces, haptics, and prosthesis.
1. Fundamental Concepts of Optimization
2. Software fundamentals for optimization
3. Basis Meaheuristic Optimization algorithms
4. Evolution Algorithms
5. Memetic Algorithms
6. Geological Optimization
7. Optimization Matlab App and Labview Toolkit
8. Equations and Ongoing Projects