Title :
Genetic drift in genetic algorithm selection schemes
Author :
Rogers, Alex ; Prügel-Bennett, Adam
Author_Institution :
Dept. of Electron. & Comput. Sci., Southampton Univ., UK
fDate :
11/1/1999 12:00:00 AM
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;
Journal_Title :
Evolutionary Computation, IEEE Transactions on
DOI :
10.1109/4235.797972
