A central receiver system is a power plant that consists of a receiver mounted atop of a central tower and a field of adjustable mirrors called heliostats. The heliostats concentrate solar radiation onto the receiver where a fluid is heated to produce electricity in a conventional thermodynamic cycle. Aiming strategies are used to assign each heliostat to an individual aim point on the receiver such that a given flux distribution on the receiver surface is reached. As uncertainties in the tracking of the heliostats exist, aiming strategies are applied that use large safety margins to avoid dangerously high flux concentrations on the receiver. This approach leads to an inefficient use of the power plant and thus economical losses. In this paper, we consider advanced methods to include these uncertainties into the design of efficient aiming strategies. To this end, we present a mixed-integer linear programming (MILP) formulation for the optimization of aiming strategies based on Gamma-robustness. In a case study, we show that the Gamma-robust optimization approach yields solutions with strong objective values and thus economical benefits while maintaining a high degree of safety. Compared to non-robust solutions, the Gamma-robust solutions achieve better objective values while guaranteeing the same safety. (C) 2019 Elsevier Ltd. All rights reserved.