Analysis of genetic algorithms using statistical mechanics

Abstract
A formalism is developed for studying genetic algorithms by considering the evolution of the distribution of fitness in the population. The effects of selection on the population are problem independent. The formalism predicts the optimal amount of selection. Crossover is solved for a model problem-finding low energy states of the one dimensional Ising spin glass. The theory is found to be in good agreement with simulations.