Maximizing the extraction of energy from wind farms with ever higher densities is becoming increasingly more important in order to achieve climate targets and simultaneously preserve nature. Improving the yield of a wind farm can be achieved by optimizing the layout, applying control, especially wake steering through yaw control has shown great results, or even combining the optimization of the layout and control into one joint optimization. In this thesis, a case study is performed on the Dutch wind farm ’IJmuiden Ver’ to investigate the real-world applicability of joint optimization. The employed method uses the genetic algorithm, capable of handling the discontinuous domain, and an improved version of the geometric yaw relationship, making coupled or nested optimization redundant. In the IJmuiden Ver case, the levelized cost of electricity (LCOE) of a joint optimized layout compared to a sequential optimized layout is around 0.3% better, even remaining around 0.2% to 0.3% better when shrinking the domain to give nature more space. This shows that joint optimization is applicable in practice and has the potential to increase the yield of a wind farm substantially without significantly increasing the computational intensity of the wind farm layout optimization problem (WFLOP).