An important goal of the theory of genetic algorithms is to build predictive models of how well
genetic algorithms are expected to perform, given a representation, a fitness landscape, and
a set of genetic operators. This paper attempts to provide pieces of such a theory, in the form
of tools that predict the behavior of genetic algorithms based on assumptions concerning the
fitness distribution of genetic operators. The fitness distribution of an operator describes the
distribution of fitness values of individuals resulting from an operator application as a …