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Conference papers

A new selection ratio for large population sizes

Fabien Teytaud 1, 2, 3
1 TANC - Algorithmic number theory for cryptology
Inria Saclay - Ile de France, LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau]
3 TAO - Machine Learning and Optimisation
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
Abstract : Motivated by parallel optimization, we study the Self-Adaptation algorithm for large population sizes. We first show that the current version of this algorithm does not reach the theoretical bounds, then we propose a very simple modification, in the selection part of the evolution process. We show that this simple modification leads to big improvement of the speed-up when the population size is large.
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Contributor : Fabien Teytaud <>
Submitted on : Sunday, February 14, 2010 - 10:12:06 AM
Last modification on : Thursday, July 8, 2021 - 3:48:37 AM
Long-term archiving on: : Friday, June 18, 2010 - 8:32:10 PM


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  • HAL Id : inria-00456335, version 1



Fabien Teytaud. A new selection ratio for large population sizes. Evostar, Apr 2010, Istanbul, Turkey. ⟨inria-00456335⟩



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