The aim of the project is to evaluate the performance of the genetic algorithm and a specific type of metamodeling (called kriging) in an engineering optimization. An automated environment for the CFD analysis is built and connected with several types of optimization strategies. The key is to find an optimal genetic algorithm’s setup, which means a good trade-off between acquired results and the optimization time. Finally, the performance of several optimization techniques is compared.