Metaheuristic Algorithms: New Methods, Evaluation, and Performance Analysis
Autor Erik Cuevas, Alberto Luque, Bernardo Morales Castañeda, Beatriz Riveraen Limba Engleză Paperback – 28 iun 2025
Preț: 1137.66 lei
Preț vechi: 1422.08 lei
-20%
Puncte Express: 1706
Carte tipărită la comandă
Livrare economică 15-21 octombrie
Livrare prin curier în România Termenul estimat este afișat lângă disponibilitate.
Transport gratuit pentru acest produs Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.
Specificații
ISBN-13: 9783031630552
ISBN-10: 3031630556
Pagini: 316
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.48 kg
Editura: Springer
ISBN-10: 3031630556
Pagini: 316
Dimensiuni: 155 x 235 x 18 mm
Greutate: 0.48 kg
Editura: Springer
Cuprins
.- 1. Introduction to Metaheuristic methods.
.- 2. A novel method for initializing populations using the Metropolis-Hastings (MH) technique.
.- 3. A measure of diversity for metaheuristic algorithms employing population-based approaches.
.- 4. Population Control in Metaheuristic Algorithms: Can Fewer Be Better?.
.- 5. Exploration Paths Derived from Trajectories Extracted from Second-Order System Responses.
.- 6. Utilizing the Moth Swarm Algorithm to Improve Image Contrast.
.- 7. Enhancing Anisotropic Diffusion Filtering via Multi-Objective Optimization.
.- 8. Fractional Fuzzy Controller Calibration Using metaheuristic Techniques.
.- 9. Striving for Optimal Equilibrium in Metaheuristic Algorithms: Is It Attainable?.
.- 2. A novel method for initializing populations using the Metropolis-Hastings (MH) technique.
.- 3. A measure of diversity for metaheuristic algorithms employing population-based approaches.
.- 4. Population Control in Metaheuristic Algorithms: Can Fewer Be Better?.
.- 5. Exploration Paths Derived from Trajectories Extracted from Second-Order System Responses.
.- 6. Utilizing the Moth Swarm Algorithm to Improve Image Contrast.
.- 7. Enhancing Anisotropic Diffusion Filtering via Multi-Objective Optimization.
.- 8. Fractional Fuzzy Controller Calibration Using metaheuristic Techniques.
.- 9. Striving for Optimal Equilibrium in Metaheuristic Algorithms: Is It Attainable?.
Textul de pe ultima copertă
This book encompasses three distinct yet interconnected objectives. Firstly, it aims to present and elucidate novel metaheuristic algorithms that feature innovative search mechanisms, setting them apart from conventional metaheuristic methods. Secondly, this book endeavors to systematically assess the performance of well-established algorithms across a spectrum of intricate and real-world problems. Finally, this book serves as a vital resource for the analysis and evaluation of metaheuristic algorithms. It provides a foundational framework for assessing their performance, particularly in terms of the balance between exploration and exploitation, as well as their capacity to obtain optimal solutions. Collectively, these objectives contribute to advancing our understanding of metaheuristic methods and their applicability in addressing diverse and demanding optimization tasks. The materials were compiled from a teaching perspective. For this reason, the book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. Additionally, engineering practitioners who are not familiar with metaheuristic computation concepts will appreciate that the techniques discussed are beyond simple theoretical tools because they have been adapted to solve significant problems that commonly arise in engineering areas.
Caracteristici
Presents and elucidates novel metaheuristic algorithms that feature innovative search mechanisms Provides a foundational framework for assessing the performance of metaheuristic Offers practical insights into the performance of optimization algorithms on real-world problems
Notă biografică
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.
Alberto Luque Chang graduated with a Bachelor's Degree in Communications and Electronics Engineering (2013), a Master of Science in Electronic Engineering and Computing (2016), and a Doctorate in Electronics and Computing Sciences (2021) in the University of Guadalajara (UdeG). He is currently a professor in the Division of Technologies for Cyber-Human Integration at the University Center for Exact Sciences and Engineering (CUCEI) of the UdeG. Likewise, since 2021, Dr. Luque is a member of the National System of Researchers, having the distinction of National Researcher Level 1. His areas of interest in research are Metaheuristic Algorithms, Artificial Intelligence, Optimization, Machine Learning and its applications. to Image Processing.
Héctor Escobar received a B.S. degree with honors in Information Systems Engineering from the Autonomous University of Sinaloa, Mexico, in 2018 and an M.S. degree in Electronics and Computer Engineering from the University of Guadalajara, Mexico, in 2021. He is part of the Universityof Guadalajara, where he is a full-time Ph.D. student in the Electronics and Computer Science program. His current research interests include Metaheuristics, computer vision, artificial intelligence, and Agent-Based Modeling.