Many industries use simulation tools for virtual product design, and there is a growing trend towards using simulation in combination with optimization algorithms. The requirements for optimization under such circumstances are often very strong, involving many design variables and constraints and a strict limitation of the number of function evaluations to a surprisingly small number (often around one thousand or less). Tuning optimization algorithms for such challenges has led to very good results obtained by variants of evolution strategies. Evolutionary algorithms are nowadays standard solvers for such applications. In the presentation, sample cases from industry are presented, their challenges are discussed in more detail. Results of an experimental comparison of contemporary evolution strategies on the BBOB test function set for a small number of function evaluations are presented and discussed, and further enhancements of contemporary evolution strategies are outlined. Our practical examples are motivated by industrial applications. A typical challenge is to find innovative solutions to a design optimization task. Based on a suitable definition of innovative solutions, an application of this concept to an airfoil design optimization task is discussed in the presentation. Discussing these applications and the variants of evolution strategies applied, the capabilities of these algorithms for optimization cases with a small number of function evaluations are illustrated.