Representations for Genetic and Evolutionary Algorithms

  • Franz Rothlauf

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 104)

Table of contents

  1. Front Matter
    Pages I-XIV
  2. Franz Rothlauf
    Pages 1-7
  3. Franz Rothlauf
    Pages 119-176
  4. Franz Rothlauf
    Pages 177-197
  5. Franz Rothlauf
    Pages 237-243
  6. Back Matter
    Pages 263-290

About this book


In the field of genetic and evolutionary algorithms (GEAs), much theory and empirical study has been heaped upon operators and test problems, but problem representation has often been taken as given. This monograph breaks with this tradition and studies a number of critical elements of a theory of representations for GEAs and applies them to the empirical study of various important idealized test functions and problems of commercial import. The book considers basic concepts of representations, such as redundancy, scaling and locality and describes how GEAs'performance is influenced. Using the developed theory representations can be analyzed and designed in a theory-guided manner. The theoretical concepts are used as examples for efficiently solving integer optimization problems and network design problems. The results show that proper representations are crucial for GEAs'success.


GEA Theorey of representation algorithm algorithms calculus communication evolution evolutionary algorithm genetic and evolutionary algorithms integer representations operator optimal communication spanning tree problem optimization tree repr

Authors and affiliations

  • Franz Rothlauf
    • 1
  1. 1.Department of Information SystemsUniversity of BayreuthBayreuthGermany

Bibliographic information

  • DOI
  • Copyright Information Physica-Verlag Heidelberg 2002
  • Publisher Name Physica-Verlag HD
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-88096-4
  • Online ISBN 978-3-642-88094-0
  • Series Print ISSN 1434-9922
  • Series Online ISSN 1860-0808
  • Buy this book on publisher's site
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