Improving the wind turbine blade design has a significant effect on the efficiency of the wind turbine. This is a challenging multi-disciplinary optimization problem. During the blade design process, the aerodynamic shapes, sizing of the structural members, and material composition must all be determined and optimized. Some previous blade design methods incorporate the wind turbine's static response with an added safety factor to account for neglected dynamic effects. Others incorporate the dynamic response, but in general is limited to a few design cases. By not fully incorporating the dynamic response of the wind turbine, the final turbine blade design is either too conservative by overemphasizing the dynamic effects or infeasible by failing to adequately account for these effects. In this work, we propose two methods which efficiently incorporate the dynamic response into the optimization routine. The first method involves iteratively calculating damage equivalent fatigue that are fixed during the optimization process. We also demonstrate the training and use of a surrogate model to efficiently estimate the fatigue damage and extreme events in the design process. This surrogate model has been generalized to be used for different rated turbines, and can predict the fatigue damage of a wind turbine with less than 5% error. In general, these alternative, more efficient methods have been shown to be an adequate replacement of the more computationally expensive method of calculating the dynamic response of the turbine within the optimization routine.