Parametric optimization varies the input parameters (the design parameters) in an attempt to drive the output parameter (the objective) in a required direction. The objective, such as the mass of the model, can be minimized or maximized. Additional parameters, such as the peak stress in the model, can serve as design constraints, requiring that they lie within a prescribed range. Parametric optimization decides which designs to consider based on the results of previous iterations of the optimization loop. The optimization ends after reaching either the maximum number of iterations or a time limit that you specified. The available objectives and design constraints include sensors and parameters (such as mass and volume) created by the Inertia Measures command. The available design parameters include geometry parameters (such as dimensions) and analysis parameters (such as loads). Objectives and design parameters are required; design constraints are optional. | |||||||||