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  • © 2018

Evolutionary Algorithms, Swarm Dynamics and Complex Networks

Methodology, Perspectives and Implementation

  • Includes recent research in Complex Networks and Evolutionary Dynamics
  • Highlights the mutual relations between the dynamics of evolutionary algorithms, complex networks, and CML (Coupled Map Lattices) systems
  • Shows how these relations can be used to simulate spatiotemporal deterministic chaos
  • Includes supplementary material: sn.pub/extras

Part of the book series: Emergence, Complexity and Computation (ECC, volume 26)

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Table of contents (15 chapters)

  1. Front Matter

    Pages i-xxii
  2. Theory

    1. Front Matter

      Pages 1-1
    2. Evolutionary Dynamics and Its Network Visualization - Selected Examples

      • Orkhan Yarakhmedov, Victor Polyakh, Ivan Chernogorov, Ivan Zelinka
      Pages 31-63
  3. Applications

    1. Front Matter

      Pages 65-65
    2. Differential Evolution Dynamics Modeled by Social Networks

      • Lenka Skanderová, Ivan Zelinka
      Pages 67-100
    3. Conversion of SOMA Algorithm into Complex Networks

      • Lukáš Tomaszek, Ivan Zelinka
      Pages 101-114
    4. Analysis of SOMA Algorithm Using Complex Network

      • Lukáš Tomaszek, Ivan Zelinka
      Pages 115-129
    5. Improvement of SOMA Algorithm Using Complex Networks

      • Lukáš Tomaszek, Ivan Zelinka
      Pages 131-143
    6. Complex Networks in Particle Swarm

      • Michal Pluhacek, Roman Šenkeřík, Adam Viktorin, Tomas Kadavy
      Pages 145-159
    7. Randomization and Complex Networks for Meta-Heuristic Algorithms

      • Roman Šenkeřík, Ivan Zelinka, Michal Pluhacek, Adam Viktorin, Jakub Janostik, Zuzana Kominkova Oplatkova
      Pages 177-194
    8. Gallery of Evolutionary Networks

      • Ivan Zelinka, Roman Šenkeřík, Michal Pluháček
      Pages 195-210
  4. Miscellanies

    1. Front Matter

      Pages 211-211
    2. Swarm Virus, Evolution, Behavior and Networking

      • Lubomir Sikora, Ivan Zelinka
      Pages 213-239
    3. Simple Networks on Complex Cellular Automata: From de Bruijn Diagrams to Jump-Graphs

      • Genaro J. Martínez, Andrew Adamatzky, Bo Chen, Fangyue Chen, Juan C. Seck-Tuoh-Mora
      Pages 241-264
    4. Dynamic Analysis of Genetic Regulatory Networks with Delays

      • Zhi-Hong Guan, Guang Ling
      Pages 285-309
    5. Frontiers

      • Ivan Zelinka
      Pages 311-312

About this book

Evolutionary algorithms constitute a class of well-known algorithms, which are designed based on the Darwinian theory of evolution and Mendelian theory of heritage. They are partly based on random and partly based on deterministic principles. Due to this nature, it is challenging to predict and control its performance in solving complex nonlinear problems. Recently, the study of evolutionary dynamics is focused not only on the traditional investigations but also on the understanding and analyzing new principles, with the intention of controlling and utilizing their properties and performances toward more effective real-world applications. In this book, based on many years of intensive research of the authors, is proposing novel ideas about advancing evolutionary dynamics towards new phenomena including many new topics, even the dynamics of equivalent social networks. In fact, it includes more advanced complex networks and incorporates them with the CMLs (coupled map lattices), whichare usually used for spatiotemporal complex systems simulation and analysis, based on the observation that chaos in CML can be controlled, so does evolution dynamics. All the chapter authors are, to the best of our knowledge, originators of the ideas mentioned above and researchers on evolutionary algorithms and chaotic dynamics as well as complex networks, who will provide benefits to the readers regarding modern scientific research on related subjects. 

Editors and Affiliations

  • Department of Computer Science, Faculty of Electrical Engineering and Computer Science VŠB-TUO, Ostrava, Poruba, Czech Republic

    Ivan Zelinka

  • Department of Electronic Engineering, City University of Hong Kong, Kowloon, Hong Kong, China

    Guanrong Chen

Bibliographic Information

  • Book Title: Evolutionary Algorithms, Swarm Dynamics and Complex Networks

  • Book Subtitle: Methodology, Perspectives and Implementation

  • Editors: Ivan Zelinka, Guanrong Chen

  • Series Title: Emergence, Complexity and Computation

  • DOI: https://doi.org/10.1007/978-3-662-55663-4

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag GmbH Germany 2018

  • Hardcover ISBN: 978-3-662-55661-0Published: 11 December 2017

  • Softcover ISBN: 978-3-662-57247-4Published: 04 September 2018

  • eBook ISBN: 978-3-662-55663-4Published: 25 November 2017

  • Series ISSN: 2194-7287

  • Series E-ISSN: 2194-7295

  • Edition Number: 1

  • Number of Pages: XXII, 312

  • Number of Illustrations: 39 b/w illustrations, 155 illustrations in colour

  • Topics: Complexity, Applications of Graph Theory and Complex Networks

Buy it now

Buying options

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