Fitness landscape analysis and image filter evolution using functional-level CGP

Abstract

This work analyzes fitness landscapes for the image filter design problem approached using functional-level Cartesian Genetic Programming. Smoothness and ruggedness of fitness landscapes are investigated for five genetic operators. It is shown that the mutation operator and the single-point crossover operator generate the smoothest landscapes and thus they are useful for practical applications in this area. In contrast to the gate-level evolution, a destructive behavior of a simple crossover operator has not been confirmed. © Springer-Verlag Berlin Heidelberg 2007.