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.
The work described in this paper was done within the Josef Ressel centre for heuristic optimization sponsored by the Austrian Research Promotion Agency (FFG).
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Affenzeller, M., Winkler, S., Beham, A., Wagner, S. (2009). On the Influence of Selection Schemes on the Genetic Diversity in Genetic Algorithms. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory - EUROCAST 2009. EUROCAST 2009. Lecture Notes in Computer Science, vol 5717. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04772-5_100
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DOI: https://doi.org/10.1007/978-3-642-04772-5_100
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