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Analysis and Comparison of Metaheuristics

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  • © 2023

Overview

Authors:
  1. Erik Cuevas

    1. CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

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  2. Omar Avalos

    1. CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

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  3. Jorge Gálvez

    1. CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

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  • Presents a comparative perspective of current metaheuristic developments
  • Includes effective applications to several complex problems
  • Gives an introduction to Analysis and Comparison of Metaheuristics from a teaching perspective

Part of the book series: Studies in Computational Intelligence (SCI, volume 1063)

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Table of contents (8 chapters)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Fundamentals of Metaheuristic Computation

    • Erik Cuevas, Omar Avalos, Jorge Gálvez
    Pages 1-9

  3. A Comparative Approach for Two-Dimensional Digital IIR Filter Design Applying Different Evolutionary Computational Techniques

    • Erik Cuevas, Omar Avalos, Jorge Gálvez
    Pages 11-36

  4. Comparison of Metaheuristics for Chaotic Systems Estimation

    • Erik Cuevas, Omar Avalos, Jorge Gálvez
    Pages 37-61

  5. Comparison Study of Novel Evolutionary Algorithms for Elliptical Shapes in Images

    • Erik Cuevas, Omar Avalos, Jorge Gálvez
    Pages 63-87

  6. IIR System Identification Using Several Optimization Techniques: A Review Analysis

    • Erik Cuevas, Omar Avalos, Jorge Gálvez
    Pages 89-104

  7. Fractional-Order Estimation Using via Locust Search Algorithm

    • Erik Cuevas, Omar Avalos, Jorge Gálvez
    Pages 105-119

  8. Comparison of Optimization Techniques for Solar Cells Parameter Identification

    • Erik Cuevas, Omar Avalos, Jorge Gálvez
    Pages 121-167

  9. Comparison of Metaheuristics Techniques and Agent-Based Approaches

    • Erik Cuevas, Omar Avalos, Jorge Gálvez
    Pages 169-220
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Keywords

About this book

This book presents a comparative perspective of current metaheuristic developments, which have proved to be effective in their application to several complex problems. The study of biological and social entities such as animals, humans, or insects that manifest a cooperative behavior has produced several computational models in metaheuristic methods. Although these schemes emulate very different processes or systems, the rules used to model individual behavior are very similar. Under such conditions, it is not clear to identify which are the advantages or disadvantages of each metaheuristic technique. The book is 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. It is appropriate for courses such as Artificial Intelligence, Electrical Engineering, Evolutionary Computation. The book is also useful for researchers from the evolutionary and engineering communities. Likewise, engineer practitioners, who are not familiar with metaheuristic computation concepts, will appreciate that the techniques discussed are beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise in engineering areas.

Authors and Affiliations

  • CUCEI, Universidad de Guadalajara, Guadalajara, Mexico

    Erik Cuevas, Omar Avalos, Jorge Gálvez

Bibliographic Information

  • Book Title: Analysis and Comparison of Metaheuristics

  • Authors: Erik Cuevas, Omar Avalos, Jorge Gálvez

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-031-20105-9

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

  • Hardcover ISBN: 978-3-031-20104-2Published: 03 November 2022

  • Softcover ISBN: 978-3-031-20107-3Published: 04 November 2023

  • eBook ISBN: 978-3-031-20105-9Published: 02 November 2022

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XIV, 220

  • Number of Illustrations: 18 b/w illustrations, 29 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

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