Genetic drift in genetic algorithm selection schemes
Alex Rogers, Adam Prügel‐Bennett · IEEE Transactions on Evolutionary Computation · 1999
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 (/spl mu/+/spl lambda/) evolution strategies. The effects of changing genetic drift on the convergence of a GA are demonstrated empirically.