Model predictive torque and flux control has shown some advantages over the classical methods. However, one of the challenges that still need to be investigated is the establishment of a control balance between the torque and flux which leads to better switching state selection. Traditionally, a weighting factor is used in the classical model predictive control (MPC). There are some new techniques that tried to avoid using a weighting factor in order to select the optimal switching state. However, in most of them, new optimization problems are added to the method. In this research, a simple discrete optimization technique is proposed for weighting factor and switching state optimization. The proposed method can be applied to the full range of operating points. The simulation and experimental results show the validity of the proposed method.