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A timing analysis of convergence to fitness sharing equilibrium

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1498))

Abstract

Fitness sharing has been shown to be an effective niching mechanism in genetic algorithms (GAs). Sharing allows GAs to maintain multiple, cooperating “species” in a single population for many generations under severe selective pressure. While recent studies have shown that the maintenance time for niching equilibrium is long, it has never been shown that the time it takes to reach equilibrium is sufficiently fast. While experiments indicate that selection under fitness sharing drives the population to equilibrium just as fast and as effectively as selection alone drives the simple GA to a uniform population, we can now show analytically that this is the case.

Professor Horn's efforts were supported by NASA under contract number NGT50873. Professor Goldberg's contribution was sponsored by the Air Force Office of Scientific Research, Air Force Materiel Command, USAF, under grants F49620-94-1-0103, F49620-95-1-0338, and F49620-97-1-0050. The US Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon. The views and conclusions contained herein are the authors' and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Air Force Office of Scientific Research or the U. S. Government.

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Agoston E. Eiben Thomas Bäck Marc Schoenauer Hans-Paul Schwefel

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© 1998 Springer-Verlag Berlin Heidelberg

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Horn, J., Goldberg, D.E. (1998). A timing analysis of convergence to fitness sharing equilibrium. In: Eiben, A.E., Bäck, T., Schoenauer, M., Schwefel, HP. (eds) Parallel Problem Solving from Nature — PPSN V. PPSN 1998. Lecture Notes in Computer Science, vol 1498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0056846

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  • DOI: https://doi.org/10.1007/BFb0056846

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65078-2

  • Online ISBN: 978-3-540-49672-4

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