Evolutionary Computation Techniques: A Comparative Perspective - Cuevas, Erik;Osuna, Valentín;Oliva, Diego
76,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in 6-10 Tagen
payback
38 °P sammeln
  • Broschiertes Buch

This book compares the performance of various evolutionary computation (EC) techniques when they are faced with complex optimization problems extracted from different engineering domains. Particularly focusing on recently developed algorithms, it is designed so that each chapter can be read independently. Several comparisons among EC techniques have been reported in the literature, however, they all suffer from one limitation: their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors,…mehr

Andere Kunden interessierten sich auch für
Produktbeschreibung
This book compares the performance of various evolutionary computation (EC) techniques when they are faced with complex optimization problems extracted from different engineering domains. Particularly focusing on recently developed algorithms, it is designed so that each chapter can be read independently. Several comparisons among EC techniques have been reported in the literature, however, they all suffer from one limitation: their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. In each chapter, a complex engineering optimization problem is posed, and then a particular EC technique is presented as the best choice, according to its search characteristics. Lastly, a set of experiments is conducted in order to compare its performance to other popular EC methods.
Autorenporträt
Dr. Erik Cuevas received his B.S. degree with distinction in Electronics and Communications Engineering from the University of Guadalajara, Mexico, in 1995, the M.Sc. degree in Industrial Electronics from ITESO, Mexico, in 2000, and the Ph.D. degree from Freie Universität Berlin, Germany in 2006. Since 2006 he has been with the University of Guadalajara, where he is currently a full-time Professor in the Department of Computer Science. Since 2008, he is a member of the Mexican National Research System (SNI III). He is the author of several books and articles. His current research interest includes Meta-heuristics, computer vision, and mathematical methods. He serves as an editor in Expert System with Applications, ISA Transactions, and Applied Soft Computing, Applied Mathematical Modeling and Mathematics and Computers in Simulation. Daniel Zaldivar graduated from the University of Guadalajara, Mexico in 1995 with a B.S. degree in Electronics and Communications Engineering. Later, in 2000, he earned his M.Sc. degree in Industrial Electronics from ITESO, Mexico, and in 2006 he received his Ph.D. degree from Freie Universität Berlin, Germany. Since then, he has been employed as a full-time Professor in the Department of Computer Science at the University of Guadalajara, where he currently holds his position. Ernesto Ayala, originally from León, Guanajuato was born in 1982. He received the title of Electrical Mechanical Engineer in 2017 and in 2019 the master's degree in Applied Computing at the University of Guadalajara. He is currently a PhD candidate in Electronics and Computing Sciences. Since 2018, he has been teaching curricular courses in Robotics Engineering and Electronic Engineering in the Division of Technologies for Cyber-human Integration of the University Center for Exact Sciences and Engineering. His area of expertise is computer vision and evolutionary computing. Mr. Ayala collaborates with a research group atthe University of Guadalajara focused on the development of ecological and autonomous driving vehicles. Oscar González received his B.S. with distinction in Electronic Engineering and Communications from the University of Guadalajara, Mexico, in 2022. During the COVID-19 pandemic, he was a member of the advisory committee for the COVID-19 pandemic of the University of Guadalajara. For his contributions and studies on COVID-19, he has been awarded the Irene Robledo García Award, the highest distinction of the University of Guadalajara for social service in 2022. Fernando Vega received the title of technical career in electricity by C.B.E.T.I.S. in 2014. Obtained a B.S. degree in Mechatronics from the National Technologist of Mexico, campus Culiacan, Mexico, in 2019. He is part of the University of Guadalajara, a full-time student M.S. in the Electronics and Computer Science program. His current research interests include motors design, electric vehicle design, Metaheuristics.