Abstract
Simple statistical techniques are investigated to support Cluster- Oriented Genetic Algorithm processes. In a real world application, this analysis improves efficiency by reducing effort relating to exploration of multiple visual representations. The preliminary results suggest that the designer can easily be guided towards interesting areas of high performance regions by viewing the most appropriate two- and three-dimensional plots.