Evolutionary Computation for Dynamic Optimization Problems

  • Shengxiang Yang
  • Xin Yao
Conference proceedings

Part of the Studies in Computational Intelligence book series (SCI, volume 490)

Table of contents

  1. Front Matter
    Pages 1-24
  2. Fundamentals

    1. Front Matter
      Pages 1-1
    2. Shengxiang Yang, Trung Thanh Nguyen, Changhe Li
      Pages 3-37
    3. Trung Thanh Nguyen, Shengxiang Yang, Juergen Branke, Xin Yao
      Pages 39-64
    4. Philipp Rohlfshagen, Xin Yao
      Pages 65-84
  3. Algorithm Design

    1. Front Matter
      Pages 107-107
    2. Hongfeng Wang, Shengxiang Yang
      Pages 137-170
    3. Enrique Alba, Hajer Ben-Romdhane, Saoussen Krichen, Briseida Sarasola
      Pages 171-191
  4. Theoretical Analysis

    1. Front Matter
      Pages 219-219
    2. Philipp Rohlfshagen, Per Kristian Lehre, Xin Yao
      Pages 221-240
    3. Hendrik Richter
      Pages 269-297
    4. Iulia Maria Comsa, Crina Grosan, Shengxiang Yang
      Pages 299-313
  5. Applications

    1. Front Matter
      Pages 315-315
    2. Maksud Ibrahimov, Arvind Mohais, Maris Ozols, Sven Schellenberg, Zbigniew Michalewicz
      Pages 433-463
  6. Back Matter
    Pages 465-469

About these proceedings


This book provides a compilation on the state-of-the-art and recent advances of evolutionary computation for dynamic optimization problems. The motivation for this book arises from the fact that many real-world optimization problems and engineering systems are subject to dynamic environments, where changes occur over time.

Key issues for addressing dynamic optimization problems in evolutionary computation, including fundamentals, algorithm design, theoretical analysis, and real-world applications, are presented. "Evolutionary Computation for Dynamic Optimization Problems" is a valuable reference to scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, nature- and bio-inspired computing, and evolutionary computation.


Computational Intelligence Dynamic Optimization Problems Evolutionary Algorithms Hybrid Intelligent Systems Meta-Heuristics Swarm Intelligence

Editors and affiliations

  • Shengxiang Yang
    • 1
  • Xin Yao
    • 2
  1. 1., School of Computer Science and InformatiDe Montfort UniversityLeicesterUnited Kingdom
  2. 2., School of Computer ScienceUniversity of BirminghamBirminghamUnited Kingdom

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-642-38415-8
  • Online ISBN 978-3-642-38416-5
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site
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