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Metaheuristic Computation: A Performance Perspective (eBook)

Artikelnummer: 978-3-030-58100-8
Einband: PDF
Verfügbarkeit: Download, sofort verfügbar (Link per E-Mail)
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This book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. Metaheuristic search methods are so numerous and varied in terms of design and potential applications; however, for such an abundant family of optimization techniques, there seems to be a question which needs to be answered: Which part of the design in a metaheuristic algorithm contributes more to its better performance? Several works that compare the performance among metaheuristic approaches have been reported in the literature. Nevertheless, they suffer from one of the following limitations: (A)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.  (B) Their conclusions consider only the comparison of their final results which cannot evaluate the nature of a good or bad balance between exploration and exploitation. The objective of this book is to compare the performance of various metaheuristic techniques when they are faced with complex optimization problems extracted from different engineering domains. The material has been compiled from a teaching perspective.


This book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. Metaheuristic search methods are so numerous and varied in terms of design and potential applications; however, for such an abundant family of optimization techniques, there seems to be a question which needs to be answered: Which part of the design in a metaheuristic algorithm contributes more to its better performance? Several works that compare the performance among metaheuristic approaches have been reported in the literature. Nevertheless, they suffer from one of the following limitations: (A)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.  (B) Their conclusions consider only the comparison of their final results which cannot evaluate the nature of a good or bad balance between exploration and exploitation. The objective of this book is to compare the performance of various metaheuristic techniques when they are faced with complex optimization problems extracted from different engineering domains. The material has been compiled from a teaching perspective.


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VerlagSpringer International Publishing
EinbandPDF
Erscheinungsjahr2020
Seitenangabe269 S.
AusgabekennzeichenEnglisch
AbbildungenXIV, 269 p. 93 illus., 31 illus. in color.
Masse10'073 KB
PlattformPDF
ReiheIntelligent Systems Reference Library; Intelligent Technologies and Robotics; Intelligent Technologies and Robotics
AutorCuevas, Erik / Diaz, Primitivo / Camarena, Octavio

Alle Bände der Reihe "Intelligent Systems Reference Library; Intelligent Technologies and Robotics; Intelligent Technologies and Robotics (R0)"

Über den Autor Erik Cuevas

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. A list of his books and publications can be seen in the CV attached to this application. 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. Alma Rodriguez earned her Bachelor of Science in Industrial Engineering and her Master's degree from CETI, Mexico, in 2005 and 2007, respectively. She went on to achieve her Doctorate in Engineering from the Universidad de Guadalajara, located in Guadalajara, Mexico, in 2021. Dr. Rodriguez has made her mark as an author of numerous engineering-related scientific publications. She contributed as a co-author to the publication "Recent Metaheuristic Computation Schemes in Engineering," released by Springer International Publishing. Her research primarily focuses on the areas of Metaheuristic Algorithms, Supplier Selection, Inventory Theory, and the broader field of optimization.Beatriz Rivera received a B.S. degree with distinction in Computer Engineering from UNIVA, México, a M.Sc. degree in Engineering Systems from UANL, México. Since 2014, she has been with The University of Guadalajara, where she is currently a Professor and enrolled in the Ph.D. program in Electronics and Computer Science. Her current research interests are metaheuristic algorithms and artificial intelligence. Jesús López obtained a bachelor's degree in Communications and Electronics Engineering in 2009 and a Master of Science degree in Electronic and Computer Engineering in 2014 from Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI) of the University of Guadalajara, Mexico. He is currently pursuing a Ph. D. in Science degree in Electronic and Computer Engineering from 2021 at the University of Guadalajara. Collaborator in the development of two patents: "Magnetic levitator system for balancing a biped robot" and "Variable transmission system based on gear assemblies forming a truncated sphere". His research interests include metaheuristics algorithms, artificial intelligence, robotics topics, artificial vision, and their applications. Carlos Guzmán received the bachelor's degree in Mechatronics Engineering from Universidad Politécnica de Sinaloa, Mexico in 2020 and a M.Sc. degree in Electronic and Computer Engineering in 2023 from the University of Guadalajara, Mexico. He is currently pursuing a Ph.D degree in Electronics and Computer Science at the University of Guadalajara, Mexico. His research interests include artificial vision and their applications.

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