The Simple Genetic Algorithm: Foundations and Theory
The Simple Genetic Algorithm: Foundations and Theory
Group properties of crossover and mutation
Evolutionary Computation
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory
A Normed Space of Genetic Operators with Applications to Scalability Issues
Evolutionary Computation
On the movement of vertex fixed points in the simple GA
Proceedings of the 11th workshop proceedings on Foundations of genetic algorithms
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We study an infinite population model for the genetic algorithm, where the iteration of the algorithm corresponds to an iteration of a map G. The map G is a composition of a selection operator and a mixing operator, where the latter models effects of both mutation and crossover. We examine the hyperbolicity of fixed points of this model. We show that for a typical mixing operator all the fixed points are hyperbolic.