A Central Limit Theorem for the Population Process of Genetic Algorithms
Stefan Voget
Institut für Mathematik, Universität Hildesheim,
Marienburger Platz 22, D-31141 Hildesheim, Germany
Abstract
A genetic algorithm (GA) is a stochastic search and optimization algorithm that works by iterative application of several evolutionary operators on populations of solutions. We introduce a central limit theorem for the population process when population size grows. The theorem approximates a GA by a continuous gaussian process. This leads to a numerical method for the examination of the algorithm. In some simple examples we present applications of the method.
