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On the Influence of Selection Schemes on the Genetic Diversity in Genetic Algorithms

  • Michael Affenzeller
  • Stephan Winkler
  • Andreas Beham
  • Stefan Wagner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5717)

Abstract

This paper discusses some aspects of the general convergence behavior of genetic algorithms. Careful attention is given to how different selection strategies influence the progress of genetic diversity in populations. For being able to observe genetic diversity over time measures are introduced for estimating pairwise similarities as well as similarities among populations; these measures allow different perspectives to the similarity distribution of a genetic algorithm’s population during its execution. The similarity distribution of populations is illustrated exemplarily on the basis of some routing problem instances.

Keywords

Genetic Algorithm Travel Salesman Problem Travel Salesman Problem Success Ratio Premature Convergence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Michael Affenzeller
    • 1
  • Stephan Winkler
    • 1
  • Andreas Beham
    • 1
  • Stefan Wagner
    • 1
  1. 1.Heuristic and Evolutionary Algorithms Laboratory School of Informatics, Communications and MediaUpper Austrian University of Applied SciencesHagenbergAustria

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