Usually the optimisation of components is a complex task. It is often characterised by multi-criteria and mostly contradictory requirements. Furthermore one doesn`t know or only with high inaccuracy, how the parameters influence the target criteria. Classical optimisation procedures, which typically assume special characteristics of the solution space, are only conditionally applicable therefore for this task. Evolutionary algorithms use the natural evolution methods for optimisation. The created solutions are gradually varied (by mutation and recombination) and are selected ac-cording to their degree of requirements fulfilment ("fitness"). In this way, the solution space is searched for the optimum. It is well known that about 75% of the costs of a product are already determined within the product development departments. By the integration of design, numeric calculation, and evolutionary algorithms, a tool is given to the designer that allows him to optimise the component already in the early phases of product development and so to contribute to an effective reduc-tion of costs.