On Representation and Genetic Operators in Evolutionary Algorithms

Abstract

The application of evolutionary algorithms (EAs) requires as a basic design decision the choice of a suitable representation of the variable space and appropriate genetic operators. In practice mainly problemspecific representations with specific genetic operators and miscellaneous extensions can be observed. In this connection it attracts attention that hardly any formal requirements on the genetic operators are stated. In this article we first formalize the representation problem and then propose a package of requirements to guide the design of genetic operators. By the definition of distance measures on the geno- and phenotype space it is possible to integrate problem-specific knowledge into the genetic operators. As an example we show how this package of requirements can be used to design a genetic programming (GP) system for finding Boolean functions.