DocumentCode
1254582
Title
Genetic drift in genetic algorithm selection schemes
Author
Rogers, Alex ; Prügel-Bennett, Adam
Author_Institution
Dept. of Electron. & Comput. Sci., Southampton Univ., UK
Volume
3
Issue
4
fYear
1999
fDate
11/1/1999 12:00:00 AM
Firstpage
298
Lastpage
303
Abstract
A method for calculating genetic drift in terms of changing population fitness variance is presented. The method allows for an easy comparison of different selection schemes and exact analytical results are derived for traditional generational selection, steady-state selection with varying generation gap, a simple model of Eshelman´s CHC algorithm (1991), and (μ+λ) evolution strategies. The effects of changing genetic drift on the convergence of a GA are demonstrated empirically
Keywords
convergence; genetic algorithms; (μ+λ) evolution strategies; Eshelman´s CHC algorithm; genetic drift; population fitness variance; selection schemes; steady-state selection; traditional generational selection; varying generation gap; Absorption; Algorithm design and analysis; Analysis of variance; Convergence; Frequency; Genetic algorithms; Performance analysis; Sampling methods; Steady-state; Stochastic processes;
fLanguage
English
Journal_Title
Evolutionary Computation, IEEE Transactions on
Publisher
ieee
ISSN
1089-778X
Type
jour
DOI
10.1109/4235.797972
Filename
797972
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