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Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications

  • Book
  • © 2021

Overview

Authors:
  1. Modestus O. Okwu

    1. Department of Mechanical and Industrial Engineering Technology, University of Johannesburg, Auckland Park, South Africa

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    You can also search for this author in PubMed   Google Scholar

  2. Lagouge K. Tartibu

    1. Department of Mechanical and Industrial Engineering Technology, University of Johannesburg, Auckland Park, South Africa

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • Introduction to metaheuristic techniques and algorithms, biomimicry and nature-inspired algorithms with swarm intelligence and presents the basics of the algorithms
  • Provides a guide of how to develop algorithms from nature-inspired systems and to solve real-life complex stochastic problems
  • Includes a list of real-life problems, model development with solution procedure from classical techniques, metaheuristic, and swarm intelligence

Part of the book series: Studies in Computational Intelligence (SCI, volume 927)

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-xii
    Download chapter PDF

  2. Introduction to Optimization

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 1-4

  3. Particle Swarm Optimisation

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 5-13

  4. Artificial Bee Colony Algorithm

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 15-31

  5. Ant Colony Algorithm

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 33-41

  6. Grey Wolf Optimizer

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 43-52

  7. Whale Optimization Algorithm (WOA)

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 53-60

  8. Firefly Algorithm

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 61-69

  9. Bat Algorithm

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 71-84

  10. Ant Lion Optimization Algorithm

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 85-94

  11. Grasshopper Optimisation Algorithm (GOA)

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 95-104

  12. Butterfly Optimization Algorithm

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 105-114

  13. Moths–Flame Optimization Algorithm

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 115-123

  14. Genetic Algorithm

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 125-132

  15. Artificial Neural Network

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 133-145

  16. Future of Nature Inspired Algorithm, Swarm and Computational Intelligence

    • Modestus O. Okwu, Lagouge K. Tartibu
    Pages 147-151

  17. Back Matter

    Pages 153-192
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Keywords

About this book

This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examplesincluded in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.

Authors and Affiliations

  • Department of Mechanical and Industrial Engineering Technology, University of Johannesburg, Auckland Park, South Africa

    Modestus O. Okwu

  • Department of Mechanical and Industrial Engineering Technology, University of Johannesburg, Auckland Park, South Africa

    Lagouge K. Tartibu

Bibliographic Information

  • Book Title: Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications

  • Authors: Modestus O. Okwu, Lagouge K. Tartibu

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-030-61111-8

  • 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 2021

  • Hardcover ISBN: 978-3-030-61110-1Published: 14 November 2020

  • Softcover ISBN: 978-3-030-61113-2Published: 14 November 2021

  • eBook ISBN: 978-3-030-61111-8Published: 13 November 2020

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XII, 192

  • Number of Illustrations: 20 b/w illustrations, 92 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

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