Modelling the Dynamics of a Steady State Genetic Algorithm

A comparison is made between the dynamics of steady state and generational genetic algorithms using the statistical mechanics approach developed by Prugel-Bennett, Shapiro and Rattray. It is shown that the loss of variance of the population under steady state selection - genetic drift - occurs at twice the rate of generational selection. By considering a simple ones counting problem with selection and mutation, it is shown that, with weak selection, the steady state genetic algorithm can reproduce the dynamics of the generational genetic algorithm at half the computational cost in terms of function evaluations