An optimization estimates the highest-scoring values of the output parameters from an approximation based on specified input parameter values and your objectives and constraints. A parametric optimization can be run on an approximation model in Results Analytics. Instead of directly running an optimization over a simulation, it is more computationally efficient to equally sample the entire design space of the simulation model, build an approximation model, and perform an optimization over this approximation model for your required objectives and constraints. You can quickly run optimizations over all types of approximations available, using multiple optimization techniques. You can compare the results of an optimization run with other design alternatives in the analytics case to arrive at the optimum design for your required objectives and constraints. | |||||||||||