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New Metaheuristic Schemes: Mechanisms and Applications

  • Book
  • © 2024

Overview

Authors:
  1. Erik Cuevas

    1. Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI), Universidad de Guadalajara, Guadalajara, Mexico

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  2. Daniel Zaldívar

    1. Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI), University of Guadalajara, Guadalajara, Mexico

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  3. Marco Pérez-Cisneros

    1. Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI), Universidad de Guadalajara, Guadalajara, Mexico

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  • Considers different new metaheuristic methods and practical applications
  • Presents new alternative metaheuristic developments effective in their application to several complex problems
  • Bridges the gap between recent metaheuristic techniques and interesting engineering problems

Part of the book series: Intelligent Systems Reference Library (ISRL, volume 246)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Introduction to Metaheuristic Schemes: Characteristics, Properties, and Importance in Solving Optimization Problems

    • Erik Cuevas, Daniel Zaldívar, Marco Pérez-Cisneros
    Pages 1-9

  3. Exploring the Potential of Agent Systems for Metaheuristics

    • Erik Cuevas, Daniel Zaldívar, Marco Pérez-Cisneros
    Pages 11-74

  4. Dynamic Multimodal Function Optimization: An Evolutionary-Mean Shift Approach

    • Erik Cuevas, Daniel Zaldívar, Marco Pérez-Cisneros
    Pages 75-108

  5. Trajectory-Driven Metaheuristic Approach Using a Second-Order Model

    • Erik Cuevas, Daniel Zaldívar, Marco Pérez-Cisneros
    Pages 109-136

  6. Collaborative Hybrid Grey Wolf Optimizer: Uniting Synchrony and Asynchrony

    • Erik Cuevas, Daniel Zaldívar, Marco Pérez-Cisneros
    Pages 137-196

  7. Efficient Image Contrast Enhancement by Using the Moth Swarm Algorithm

    • Erik Cuevas, Daniel Zaldívar, Marco Pérez-Cisneros
    Pages 197-239

  8. Multi-objective Optimization of Anisotropic Diffusion Parameters for Enhanced Image Denoising

    • Erik Cuevas, Daniel Zaldívar, Marco Pérez-Cisneros
    Pages 241-268
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Keywords

About this book

Recently, novel metaheuristic techniques have emerged in response to the limitations of conventional approaches, leading to enhanced outcomes. These new methods introduce interesting mechanisms and innovative collaborative strategies that facilitate the efficient exploration and exploitation of extensive search spaces characterized by numerous dimensions. The objective of this book is to present advancements that discuss novel alternative metaheuristic developments that have demonstrated their effectiveness in tackling various complex problems. This book encompasses a variety of emerging metaheuristic methods and their practical applications. The content is presented from a teaching perspective, making it particularly suitable for undergraduate and postgraduate students in fields such as science, electrical engineering, and computational mathematics. The book aligns well with courses in artificial intelligence, electrical engineering, and evolutionary computation. Furthermore, the material offers valuable insights to researchers within the metaheuristic and engineering communities. Similarly, engineering practitioners unfamiliar with metaheuristic computation concepts will recognize the pragmatic value of the discussed techniques. These methods transcend mere theoretical tools that have been adapted to effectively address the significant real-world problems commonly encountered in engineering domains.

Authors and Affiliations

  • Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI), Universidad de Guadalajara, Guadalajara, Mexico

    Erik Cuevas, Marco Pérez-Cisneros

  • Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI), University of Guadalajara, Guadalajara, Mexico

    Daniel Zaldívar

Bibliographic Information

  • Book Title: New Metaheuristic Schemes: Mechanisms and Applications

  • Authors: Erik Cuevas, Daniel Zaldívar, Marco Pérez-Cisneros

  • Series Title: Intelligent Systems Reference Library

  • DOI: https://doi.org/10.1007/978-3-031-45561-2

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024

  • Hardcover ISBN: 978-3-031-45560-5Published: 07 November 2023

  • Softcover ISBN: 978-3-031-45563-6Due: 08 December 2023

  • eBook ISBN: 978-3-031-45561-2Published: 06 November 2023

  • Series ISSN: 1868-4394

  • Series E-ISSN: 1868-4408

  • Edition Number: 1

  • Number of Pages: XIV, 268

  • Number of Illustrations: 34 b/w illustrations, 43 illustrations in colour

  • Topics: Cyber-physical systems, IoT, Machine Learning, Artificial Intelligence, Computer Science, general

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