International Journal of Computational Intelligence Research (IJCIR)

Volume 1, Number 1 (2005)

 


Analysis of a Non-Generational Mutationless Evolutionary Algorithm 

for Separable Fitness Functions


Gunter Rudolph
University of Dortmund 

Department of Computer Science 

44221 Dortmund/Germany

Abstract
It is shown that the stochastic dynamics of non-generational evolutionary algorithms with binary tournament selection and gene pool recombination but without mutation is closely approximated by a stochastic process consisting of several de-coupled random walks, provided the fitness function is separable in a certain sense. This approach leads to a lower bound on the population size such that the evolutionary algorithm converges to a uniform population with globally optimal individuals for a given confidence level.
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