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Nature-Inspired Optimizers

Theories, Literature Reviews and Applications

  • Book
  • © 2020

Overview

Editors:
  1. Seyedali Mirjalili

    1. Institute for Integrated and Intelligent Systems, Griffith University, Brisbane, Australia

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    You can also search for this editor in PubMed   Google Scholar

  2. Jin Song Dong

    1. Institute for Integrated and Intelligent Systems, Griffith University, Brisbane, Australia

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    You can also search for this editor in PubMed   Google Scholar

  3. Andrew Lewis

    1. Institute for Integrated and Intelligent Systems, Griffith University, Brisbane, Australia

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    You can also search for this editor in PubMed   Google Scholar

  • Offers a comprehensive tutorial on evolutionary optimization
  • Describes the mathematical model each algorithm is based on Reports on several benchmark case studies
  • Source codes are available on a dedicated webpage

Part of the book series: Studies in Computational Intelligence (SCI, volume 811)

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xvi
    Download chapter PDF

  2. Introduction to Nature-Inspired Algorithms

    • Seyedali Mirjalili, Jin Song Dong
    Pages 1-5

  3. Ant Colony Optimizer: Theory, Literature Review, and Application in AUV Path Planning

    • Seyedali Mirjalili, Jin Song Dong, Andrew Lewis
    Pages 7-21

  4. Ant Lion Optimizer: Theory, Literature Review, and Application in Multi-layer Perceptron Neural Networks

    • Ali Asghar Heidari, Hossam Faris, Seyedali Mirjalili, Ibrahim Aljarah, Majdi Mafarja
    Pages 23-46

  5. Dragonfly Algorithm: Theory, Literature Review, and Application in Feature Selection

    • Majdi Mafarja, Ali Asghar Heidari, Hossam Faris, Seyedali Mirjalili, Ibrahim Aljarah
    Pages 47-67

  6. Genetic Algorithm: Theory, Literature Review, and Application in Image Reconstruction

    • Seyedali Mirjalili, Jin Song Dong, Ali Safa Sadiq, Hossam Faris
    Pages 69-85

  7. Grey Wolf Optimizer: Theory, Literature Review, and Application in Computational Fluid Dynamics Problems

    • Seyedali Mirjalili, Ibrahim Aljarah, Majdi Mafarja, Ali Asghar Heidari, Hossam Faris
    Pages 87-105

  8. Grasshopper Optimization Algorithm: Theory, Literature Review, and Application in Hand Posture Estimation

    • Shahrzad Saremi, Seyedehzahra Mirjalili, Seyedali Mirjalili, Jin Song Dong
    Pages 107-122

  9. Multi-verse Optimizer: Theory, Literature Review, and Application in Data Clustering

    • Ibrahim Aljarah, Majdi Mafarja, Ali Asghar Heidari, Hossam Faris, Seyedali Mirjalili
    Pages 123-141

  10. Moth-Flame Optimization Algorithm: Theory, Literature Review, and Application in Optimal Nonlinear Feedback Control Design

    • Seyed Hamed Hashemi Mehne, Seyedali Mirjalili
    Pages 143-166

  11. Particle Swarm Optimization: Theory, Literature Review, and Application in Airfoil Design

    • Seyedali Mirjalili, Jin Song Dong, Andrew Lewis, Ali Safa Sadiq
    Pages 167-184

  12. Salp Swarm Algorithm: Theory, Literature Review, and Application in Extreme Learning Machines

    • Hossam Faris, Seyedali Mirjalili, Ibrahim Aljarah, Majdi Mafarja, Ali Asghar Heidari
    Pages 185-199

  13. Sine Cosine Algorithm: Theory, Literature Review, and Application in Designing Bend Photonic Crystal Waveguides

    • Seyed Mohammad Mirjalili, Seyedeh Zahra Mirjalili, Shahrzad Saremi, Seyedali Mirjalili
    Pages 201-217

  14. Whale Optimization Algorithm: Theory, Literature Review, and Application in Designing Photonic Crystal Filters

    • Seyedehzahra Mirjalili, Seyed Mohammad Mirjalili, Shahrzad Saremi, Seyedali Mirjalili
    Pages 219-238
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Keywords

About this book

This book covers the conventional and most recent theories and applications in the area of evolutionary algorithms, swarm intelligence, and meta-heuristics. Each chapter offers a comprehensive description of a specific algorithm, from the mathematical model to its practical application. Different kind of optimization problems are solved in this book, including those related to path planning, image processing, hand gesture detection, among others.  All in all, the book offers a tutorial on how to design, adapt, and evaluate evolutionary algorithms. Source codes for most of the proposed techniques have been included as supplementary materials on a dedicated webpage.

Editors and Affiliations

  • Institute for Integrated and Intelligent Systems, Griffith University, Brisbane, Australia

    Seyedali Mirjalili, Jin Song Dong, Andrew Lewis

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