Optimization in device design is to determine the the most appropriate set of the physical and technological parameters that results in the specified performance parameters.
It could be also formulated as the set of the physical and technological parameters ranges that results in the specified performance parameters.
I think such problems can be solved machine learning as a solution selection problem.
One uses the device simulator to generate the all the performances at the possible set of input parameters and then one can use neural networks or any other optimization means for the best selection.