(i) a constrained gradient optimizer based on SLSQP or Adam, (ii) a constrained genetic algorithm (GA) optimizer based on the PyMOO library, 85 and (iii) a constrained GA based on the DEAP library. Gradient strategies are well-suited for problems with fully-continuous parameter spaces, while GA strategies are well-suited for mixed-parameter problems and fully discrete/categorical problems with large Cartesian product spaces.