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Citation

Ochoa G & Harvey I (1999) Recombination and error thresholds in finite populations. In: Banzhaf W & Reeves C (eds.) Foundations of Genetic Algorithms, Volume 5. Foundations of Genetic Algorithms, 5. 1998 Foundations of Genetic Algorithms (FOGA-5), Amsterdam, The Netherlands, 24.09.1998-28.09.1998. San Francisco, CA, USA: Morgan Kaufman, pp. 245-264.

Abstract
This paper introduces the notions of quasispecies and error threshold from molecular evolutionary biology The error threshold is a critical mutation rate beyond which the eect of selection on the population changes drastically We reproduce using GAs and hence nite populations some interesting results obtained with an analytical model using in nite populations from the evo lutionary biology literature A reformulation of a previous analytical expression which explicitly indicates the extent of the reduction in the error threshold as we move from in nite to nite populations is derived Error thresholds are shown to be lower for nite populations Moreover as in the in nite case for low muta tion rates recombination can reduce the diversity of the population and enhance overall tness For high mutation rates however recombination can push the pop ulation over the error threshold and thereby cause a loss of genetic information These results may be relevant to optimizing the explorationexploitation balance in GAs Choices for critical GA parameters such as population size mutation and recombination rates should be reconsidered in the light of this new knowledge