The paper first outlines a powertrain dynamic model whose central part is a 10-speed AT model that is based on the numerically efficient Karnopp clutch friction model. Then, the trajectory optimization approach is demonstrated based on the authors’ previous publication and employed with the aim of getting insights into the optimal shift control performance. Based on the deduced optimal shift control time traces, piecewise linear shift control profiles (clutch capacity and engine torque reduction) are defined. The optimization problem is to find design/control vector containing parameters of piecewise linear shift control profiles, which provides a trade off between shift comfort and performance. The optimization problem is solved by using state-of-the-art multi-objective genetic algorithm MOGA-II incorporated within modeFrontier environment. As an extension of the parameter optimization approach, a method for robust parameter optimization is proposed, which aims at ensuring high shift quality and reliability in the presence of transmission actuation parameter variations. The objective is to find shift control profile parameters that simultaneously minimize mean values of vehicle jerk and shift duration indices as well as their standard deviations for improved robustness against change of transmission parameters. The overall optimization approach is demonstrated first on an example of a single-transition power-on upshift and the obtained optimization results are analyzed and compared to the control trajectory optimization results used as a benchmark. The robust parameter optimization method is then applied for the same shift scenario, and results are compared with the basic (non-robust) optimization case. The analysis points out that the shift robustness can be improved by sacrificing comfort. Finally, the method is applied to a double-transition power-on downshift to illustrate its applicability for a more demanding transmission control task.