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Engineering Applications of Modern Metaheuristics

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  • © 2023

Overview

Editors:
  1. Taymaz Akan

    1. Department of Medicine, Louisiana State University Health Sciences Center, Shreveport, USA

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  2. Ahmed M. Anter

    1. Egypt-Japan University of Science and Technology (E-JUST), Alexandria, Egypt

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  3. A. Şima Etaner-Uyar

    1. Department of Software Engineering, Fatih Sultan Mehmet Vakıf University, Istanbul, Turkey

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  4. Diego Oliva

    1. Depto. de Innovación Basada en la Información y el Conocimiento, Universidad de Guadalajara, CUCEI, Guadajalara, Mexico

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  • Provides the reader with the most representative optimization tools used for scientific and engineering problems
  • Explains the algorithms used, the selected problem, and the implementation
  • Provides practical examples, comparisons, and experimental results

Part of the book series: Studies in Computational Intelligence (SCI, volume 1069)

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Table of contents (11 chapters)

  1. Front Matter

    Pages i-vi
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  2. Empirical Comparison of Heuristic Optimisation Methods for Automated Car Setup

    • Berna Kiraz, Shahriar Asta, Ender Özcan, Muhammet Köle, A. Şima Etaner-Uyar
    Pages 1-18

  3. Metaheuristic Algorithms in IoT: Optimized Edge Node Localization

    • Farzad Kiani, Amir Seyyedabbasi
    Pages 19-39

  4. JAYA Algorithm Versus Differential Evolution: A Comparative Case Study on Optic Disc Localization in Eye Fundus Images

    • J. Prakash, B. Vinoth Kumar
    Pages 41-50

  5. Minimum Transmission Power Control for the Internet of Things with Swarm Intelligence Algorithms

    • Ahmet Cevahir Cinar
    Pages 51-77

  6. An Enhanced Gradient Based Optimized Controller for Load Frequency Control of a Two Area Automatic Generation Control System

    • Nabil Anan Orka, Sheikh Samit Muhaimin, Md. Nazmush Shakib Shahi, Ashik Ahmed
    Pages 79-107

  7. A Meta-Heuristic Algorithm Based on the Happiness Model

    • Aref Yelghi, Shirmohammad Tavangari
    Pages 109-126

  8. Application of Metaheuristic Techniques for Enhancing the Financial Profitability of Wind Power Generation Systems

    • Prasun Bhattacharjee, Rabin K. Jana, Somenath Bhattacharya
    Pages 127-147

  9. Optimization of Demand Response

    • Altaf Q. H. Badar, Rajeev Arya, Diego Oliva
    Pages 149-165

  10. Fitting Curves of Ruminal Degradation Using a Metaheuristic Approach

    • Muhammed Milani
    Pages 167-177

  11. Optimizing a Real Case Assembly Line Balancing Problem Using Various Techniques

    • Nima Mirzaei, Mazyar Ghadiri Nejad
    Pages 179-191

  12. Multi-circle Detection Using Multimodal Optimization

    • Aydin Cetin, Somaiyeh Rezai, Taymaz Akan
    Pages 193-209
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Keywords

About this book

This book is a collection of various methodologies that make it possible for metaheuristics and hyper-heuristics to solve problems that occur in the real world. This book contains chapters that make use of metaheuristics techniques. The application fields range from image processing to transmission power control, and case studies and literature reviews are included to assist the reader. Furthermore, some chapters present cutting-edge methods for load frequency control and IoT implementations. In this sense, the book offers both theoretical and practical contents in the form of metaheuristic algorithms. The researchers used several stochastic optimization methods in this book, including evolutionary algorithms and Swarm-based algorithms. The chapters were written from a scientific standpoint. As a result, the book is primarily aimed at undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics, but it can also be used in courses on Artificial Intelligence, among other things. Similarly, the material may be beneficial to research in evolutionary computation and artificial intelligence communities.

Editors and Affiliations

  • Department of Medicine, Louisiana State University Health Sciences Center, Shreveport, USA

    Taymaz Akan

  • Egypt-Japan University of Science and Technology (E-JUST), Alexandria, Egypt

    Ahmed M. Anter

  • Department of Software Engineering, Fatih Sultan Mehmet Vakıf University, Istanbul, Turkey

    A. Şima Etaner-Uyar

  • Depto. de Innovación Basada en la Información y el Conocimiento, Universidad de Guadalajara, CUCEI, Guadajalara, Mexico

    Diego Oliva

Bibliographic Information

  • Book Title: Engineering Applications of Modern Metaheuristics

  • Editors: Taymaz Akan, Ahmed M. Anter, A. Şima Etaner-Uyar, Diego Oliva

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-031-16832-1

  • 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: 978-3-031-16831-4Published: 05 December 2022

  • Softcover ISBN: 978-3-031-16834-5Published: 05 December 2023

  • eBook ISBN: 978-3-031-16832-1Published: 04 December 2022

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: VI, 209

  • Number of Illustrations: 26 b/w illustrations, 70 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence, Data Engineering

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