Noise, fitness distribution, and selection intensity in genetic algorithms

Authors:
Timothy Meekhof;Terence Soule
Affiliations:
University of Idaho, Moscow, ID, USA;University of Idaho, Moscow, ID, USA
Venue:
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Year:
2011

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Abstract

Many Genetic Algorithm (GA) problems have noisy fitness functions. In this paper, we describe a mathematical model of the noise distribution after selection and then show how this model of the noise distribution can be used to model the real, underlying selection intensity of the GA population, which promises to give us a better way to model GA convergence in the presence of noise.