The aim of almost all design tasks in engineering is to determine a robust design. In order to assess the robustness, the uncertainty of input parameters has to be taken into account. The incorporation of uncertain parameters in an optimization task may succeed in an active or passive manner. In this contribution, the theoretical bases of active and of passive optimization strategies are introduced. In an active approach, also denoted as here-and-now strategy, the uncertainty for a respective design is known and the robustness can be assessed directly. Thereby, the numerical effort to determine a robust optimum can be tremendous. In a passive approach, also denoted as wait-and-see strategy, the optimal design is determined without a distinct knowledge about the uncertainty of this design. A first good shot about an optimal robust design can be determined efficiently, but a quantification of robustness is hindered. Both approaches are evaluated in detail and on the basis of the obtained results, a combined approach is elaborated. In a combined approach, the advantages should be intensified while the disadvantages should be reduced. Hence, a robust design can be identified in a numerically efficient way. The applicability of the presented approach is demonstrated by means of an example. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)