Analysis of a Non-Generational Mutationless Evolutionary Algorithm for Separable Fitness Functions | Zendy

Günter Rudolph | Zendy

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Analysis of a Non-Generational Mutationless Evolutionary Algorithm for Separable Fitness Functions

Author(s) -

Günter Rudolph

Publication year - 2005

Publication title -

international journal of computational intelligence research

Language(s) - English

Resource type - Journals

eISSN - 0974-1259

pISSN - 0973-1873

DOI - 10.5019/j.ijcir.2005.25

Subject(s) - separable space , tournament selection , selection (genetic algorithm) , population , fitness function , mathematical optimization , computer science , binary number , evolutionary algorithm , function (biology) , mutation , tournament , algorithm , stochastic process , mathematics , genetic algorithm , combinatorics , artificial intelligence , statistics , biology , gene , evolutionary biology , genetics , mathematical analysis , demography , arithmetic , sociology

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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