The research presented treats the robust design optimization (RDO) of an unmanned aerialvehicle (UAV) considering geometric uncertainty related to its production process. RDO re-quires uncertainty quantification (UQ) in a number of design points, making it computationallyexpensive. Therefore, surrogate modelling is employed to efficiently perform the optimization.The optimization is regarded as a multi-objective optimization (MOO) of expected value andvariance. The goal is to obtain a Pareto set of non-dominated solutions. Several methods areassessed by applying them to an analytical test function. Subsequently, the RDO of a UAV with forward swept planform and the validation of the resulting optimal points are performed.
