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  • © 2015

Adaptation and Hybridization in Computational Intelligence

  • Presents recent research in self-adaptation techniques in computational intelligence algorithms and applications as well as theoretical analysis
  • Provides both theoretical treatments and real-world insights gained by experience
  • Comprehensive reference for researchers, practitioners and advanced-level students interested in using computational intelligence algorithms in real-world applications

Part of the book series: Adaptation, Learning, and Optimization (ALO, volume 18)

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Table of contents (10 chapters)

  1. Front Matter

    Pages 1-10
  2. Background Information and Theoretical Foundations of Computational Intelligence

    1. Front Matter

      Pages 1-1
    2. Adaptation and Hybridization in Nature-Inspired Algorithms

      • Iztok Fister, Damjan Strnad, Xin-She Yang, Iztok Fister Jr.
      Pages 3-50
  3. Adaptation in Computational Intelligence

    1. Front Matter

      Pages 51-51
    2. Adaptation in the Differential Evolution

      • Janez Brest, AleÅ¡ Zamuda, Borko BoÅ¡ković
      Pages 53-68
    3. On the Mutation Operators in Evolution Strategies

      • Iztok Fister Jr., Iztok Fister
      Pages 69-89
    4. Study of Lagrangian and Evolutionary Parameters in Krill Herd Algorithm

      • Gai-Ge Wang, Amir H. Gandomi, Amir H. Alavi
      Pages 111-128
    5. Solutions of Non-smooth Economic Dispatch Problems by Swarm Intelligence

      • Seyyed Soheil Sadat Hosseini, Xin-She Yang, Amir H. Gandomi, Alireza Nemati
      Pages 129-146
  4. Hybridization in Computational Intelligence

    1. Front Matter

      Pages 147-147
    2. Hybrid Artificial Neural Network for Fire Analysis of Steel Frames

      • Tomaž Hozjan, Goran Turk, Iztok Fister
      Pages 149-169
    3. A Differential Evolution Algorithm with a Variable Neighborhood Search for Constrained Function Optimization

      • M. Fatih Tasgetiren, P. N. Suganthan, Sel Ozcan, Damla Kizilay
      Pages 171-184
    4. A Memetic Differential Evolution Algorithm for the Vehicle Routing Problem with Stochastic Demands

      • Yannis Marinakis, Magdalene Marinaki, Paraskevi Spanou
      Pages 185-204
    5. Modeling Nanorobot Control Using Swarm Intelligence for Blood Vessel Repair: A Rigid-Tube Model

      • Boonserm Kaewkamnerdpong, Pinfa Boonrong, Supatchaya Trihirun, Tiranee Achalakul
      Pages 205-236
  5. Back Matter

    Pages 237-237

About this book

This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI.

This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization, modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence –based algorithms.

Editors and Affiliations

  • Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia

    Iztok Fister, Iztok Fister Jr.

Bibliographic Information

  • Book Title: Adaptation and Hybridization in Computational Intelligence

  • Editors: Iztok Fister, Iztok Fister Jr.

  • Series Title: Adaptation, Learning, and Optimization

  • DOI: https://doi.org/10.1007/978-3-319-14400-9

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer International Publishing Switzerland 2015

  • Hardcover ISBN: 978-3-319-14399-6Published: 05 February 2015

  • Softcover ISBN: 978-3-319-35905-2Published: 06 October 2016

  • eBook ISBN: 978-3-319-14400-9Published: 24 January 2015

  • Series ISSN: 1867-4534

  • Series E-ISSN: 1867-4542

  • Edition Number: 1

  • Number of Pages: X, 237

  • Number of Illustrations: 41 b/w illustrations, 1 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access