Creating robust solutions by means of evolutionary algorithms

For real world problems it is often not sufficient to find solutions of high quality, but the solutions should also be robust. By robust we mean that the quality of the solution does not falter completely when a slight change of the environment occurs, or that certain deviations from the solution should be tolerated without a total loss of quality. In this paper, a number of modifications to the standard evolutionary algorithm (EA) are suggested that are supposed to lead the EA to produce more robust solutions. Some preliminary experiments are reported where the proposed approaches are compared to a standard model. As it turns out, the EA's ability to create robust solutions can be greatly enhanced even without additional function evaluations.