© 2003

Advances in Evolutionary Computing

Theory and Applications

  • Ashish Ghosh
  • Shigeyoshi Tsutsui
  • State of the art of theory and applications in Evolutionary Algorithms Contributions by established researchers in the field

  • Well-balanced between theory and applications


Part of the Natural Computing Series book series (NCS)

Table of contents

  1. Front Matter
    Pages I-XVI
  2. Theory

    1. Front Matter
      Pages 1-1
    2. Vesselin K. Vassilev, Terence C. Fogarty, Julian F. Miller
      Pages 3-44
    3. Xin Yao, Yong Liu, Ko-Hsin Liang, Guangming Lin
      Pages 45-94
    4. Trevor D. Collins
      Pages 95-116
    5. Hidefumi Sawai, Susumu Adachi, Sachio Kizu
      Pages 117-151
    6. Stefan Droste, Dirk Wiesmann
      Pages 153-173
    7. Zbigniew Michalewicz, Martin Schmidt
      Pages 193-212
    8. Isao Ono, Hajime Kita, Shigenobu Kobayashi
      Pages 213-237
    9. Jürgen Branke, Hartmut Schmeck
      Pages 239-262
    10. Hillol Kargupta
      Pages 293-319
    11. Dimitri Knjazew, David E. Goldberg
      Pages 321-350
    12. William M. Spears, Diana F. Gordon-Spears
      Pages 367-392
    13. Akiko Aizawa
      Pages 413-439
    14. Sanjeev Kumar, Peter J. Bentley
      Pages 461-477

About this book


The term evolutionary computing (EC) refers to the study of the foundations and applications of certain heuristic techniques based on the principles of natural evolution, and thus the aim when designing evolutionary algorithms (EAs) is to mimic some of the processes taking place in natural evolution.

Many researchers around the world have been developing EC methodologies for designing intelligent decision-making systems for a variety of real-world problems. This book provides a collection of 40 articles, written by leading experts in the field, containing new material on both the theoretical aspects of EC and demonstrating its usefulness in various kinds of large-scale real-world problems. Of the articles contributed, 23 articles deal with various theoretical aspects of EC and 17 demonstrate successful applications of EC methodologies.



Artificial Intelligence Artificial Life Evolutionary Computation Genetic Algorithms Heuristic Methods algorithms evolutionary algorithm

Editors and affiliations

  • Ashish Ghosh
    • 1
  • Shigeyoshi Tsutsui
    • 2
  1. 1.Machine Intelligence UnitIndian Statistical InstituteKolkataIndia
  2. 2.Department of Management InformationHannan UniversityMatsubara, OsakaJapan

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