© 2018

Nature-Inspired Algorithms and Applied Optimization

  • Xin-She Yang

Part of the Studies in Computational Intelligence book series (SCI, volume 744)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Xing-Shi He, Fan Wang, Yan Wang, Xin-She Yang
    Pages 53-67
  3. Eneko Osaba, Roberto Carballedo, Xin-She Yang, Iztok Fister Jr., Pedro Lopez-Garcia, Javier Del Ser
    Pages 69-89
  4. Zaid Abdi Alkareem Alyasseri, Ahamad Tajudin Khader, Mohammed Azmi Al-Betar, Mohammed A. Awadallah, Xin-She Yang
    Pages 91-118
  5. João Paulo Papa, Gustavo Henrique de Rosa, Xin-She Yang
    Pages 119-147
  6. Carlos Loucera, Andrés Iglesias, Akemi Gálvez
    Pages 149-169
  7. Aylin Ece Kayabekir, Gebrail Bekdaş, Sinan Melih Nigdeli, Xin-She Yang
    Pages 171-188
  8. Asma Chakri, Haroun Ragueb, Xin-She Yang
    Pages 189-216
  9. Xin-She Yang, Xing-Shi He
    Pages 245-259
  10. T. Jayabarathi, T. Raghunathan, A. H. Gandomi
    Pages 313-330

About this book


This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.


Algorithm Applied Optimization Bio-inspired Computing Bat Algorithm Convergence Analysis Cuckoo Search Economic Load Dispatch Feature Selection Firefly Algorithm Flower Pollination Algorithm Simulated Annealing Swarm Intelligence Nature-inspired Algorithm Wireless Sensor Network Particle Swarm Optimization Scheduling Metaheuristics Multi-objective Optimization No Free Lunch Theorem Vehicle Routing

Editors and affiliations

  • Xin-She Yang
    • 1
  1. 1.School of Science and TechnologyMiddlesex UniversityLondonUnited Kingdom

Bibliographic information

  • Book Title Nature-Inspired Algorithms and Applied Optimization
  • Editors Xin-She Yang
  • Series Title Studies in Computational Intelligence
  • Series Abbreviated Title Studies Comp.Intelligence
  • DOI
  • Copyright Information Springer International Publishing AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Hardcover ISBN 978-3-319-67668-5
  • Softcover ISBN 978-3-319-88465-3
  • eBook ISBN 978-3-319-67669-2
  • Series ISSN 1860-949X
  • Series E-ISSN 1860-9503
  • Edition Number 1
  • Number of Pages XI, 330
  • Number of Illustrations 14 b/w illustrations, 28 illustrations in colour
  • Topics Computational Intelligence
    Artificial Intelligence
  • Buy this book on publisher's site
Industry Sectors
Chemical Manufacturing
IT & Software
Consumer Packaged Goods
Materials & Steel
Finance, Business & Banking
Energy, Utilities & Environment
Oil, Gas & Geosciences


“This book presents recent developments in nature-inspired algorithms and optimization and includes many case studies. … The contributing authors are experts in the field from various parts of the world. This highly recommended book--a snapshot of recent research in the field of nature-inspired algorithms--would be a useful reference work for its intended audience.” (S. V. Nagaraj, Computing Reviews, September, 2018)​

“The book is rich with relevant illustrations and real-life/practical problems, where the various topics are or can be applied. The book is a comprehensive and in-depth study, and the style of presentation is remarkable. These aspects make reading this book an absolute delight.” (Sudev Naduvath, Computing Reviews, August, 2018)