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Handbook of Nature-Inspired Optimization Algorithms: The State of the Art

Volume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems

  • Book
  • © 2022

Overview

Editors:
  1. Ali Mohamed

    1. Operations Research Department, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, Egypt

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  2. Diego Oliva

    1. Department of Computer Sciences, University of Guadalajara, Guadalajara, Mexico

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    You can also search for this editor in PubMed   Google Scholar

  3. Ponnuthurai Nagaratnam Suganthan

    1. School of EEE, Nanyang Technological University, Singapore, Singapore

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  • Explains the algorithms used, selected problems, and the implementation
  • Focuses on solving single objective bound-constrained real parameter numerical optimization problems with NIOAs
  • Provides practical examples, comparisons, and experimental results

Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 212)

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About this book

The introduction of nature-inspired optimization algorithms (NIOAs), over the past three decades, helped solve nonlinear, high-dimensional, and complex computational optimization problems. NIOAs have been originally developed to overcome the challenges of global optimization problems such as nonlinearity, non-convexity, non-continuity, non-differentiability, and/or multimodality which traditional numerical optimization techniques had difficulties solving.

The main objective for this book is to make available a self-contained collection of modern research addressing the general bound-constrained optimization problems in many real-world applications using nature-inspired optimization algorithms. This book is suitable for a graduate class on optimization, but will also be useful for interested senior students working on their research projects.

Keywords

Table of contents (10 chapters)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Chaotic-SCA Salp Swarm Algorithm Enhanced with Opposition Based Learning: Application to Decrease Carbon Footprint in Patient Flow

    • Masoumeh Vali, Khodakaram Salimifard, Amir H. Gandomi, Thierry Chaussalet
    Pages 1-29

  3. Design and Performance Evaluation of Objective Functions Based on Various Measures of Fuzzy Entropies for Image Segmentation Using Grey Wolf Optimization

    • Baljit Singh Khehra, Arjan Singh, Lovepreet Kaur
    Pages 31-89

  4. Improved Artificial Bee Colony Algorithm with Adaptive Pursuit Based Strategy Selection

    • Osman Gokalp
    Pages 91-115

  5. Beetle Antennae Search Algorithm for the Motion Planning of Industrial Manipulator

    • Junwen Cui, Zhan Li
    Pages 117-134

  6. Solving Optimal Power Flow with Considering Placement of TCSC and FACTS Cost Using Cuckoo Search Algorithm

    • Benyekhlef Larouci, Houari Boudjella, Ahmed Nour El Islam Ayad, Abdelkader Si Tayeb
    Pages 135-155

  7. Parameter Estimation of Per-Unit Photovoltaic Models Using Optimization Algorithms: Comparative Study

    • H. G. G. Nunes, J. P. A. Portugal, J. A. N. Pombo, S. J. P. S. Mariano, M. R. A. Calado
    Pages 157-195

  8. Space–Time Concept in Social Network Search Algorithm

    • Siamak Talatahari, Hadi Bayzidi, Mehdi Bayzidi
    Pages 197-227

  9. Genetic Algorithm Golden Ratio Design Model for Auto Arts

    • Khaled Hossameldin Sadek Ibrahim, Ali Khater Mohamed, Ahmed Farouk
    Pages 229-242

  10. Antenna Array Design Using Differential Evolution with Ranking-Based Mutation Operators

    • Sotirios K. Goudos, Ali Wagdy Mohamed
    Pages 243-263

  11. Battle Royale Optimizer with a New Movement Strategy

    • Sara Akan, Taymaz Akan
    Pages 265-279
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Editors and Affiliations

  • Operations Research Department, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, Egypt

    Ali Mohamed

  • Department of Computer Sciences, University of Guadalajara, Guadalajara, Mexico

    Diego Oliva

  • School of EEE, Nanyang Technological University, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

Bibliographic Information

  • Book Title: Handbook of Nature-Inspired Optimization Algorithms: The State of the Art

  • Book Subtitle: Volume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems

  • Editors: Ali Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan

  • Series Title: Studies in Systems, Decision and Control

  • DOI: https://doi.org/10.1007/978-3-031-07512-4

  • 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 2022

  • Hardcover ISBN: 978-3-031-07511-7Published: 01 September 2022

  • Softcover ISBN: 978-3-031-07514-8Published: 02 September 2023

  • eBook ISBN: 978-3-031-07512-4Published: 31 August 2022

  • Series ISSN: 2198-4182

  • Series E-ISSN: 2198-4190

  • Edition Number: 1

  • Number of Pages: X, 279

  • Number of Illustrations: 21 b/w illustrations, 73 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

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