Optimization Setup for the Sequential Nonlinear Programming (Gradient) Optimizer
Following is the procedure for setting up an optimization analysis using the Sequential Nonlinear Programming (Gradient) Optimizer or SNLP Optimizer. Once you have created a setup, you can Copy and Paste it, and then make changes to the copy, rather than redoing the whole process for minor changes.
- Set up the variables you want to optimize in the Design Properties dialog box.
- From the Maxwell 3D/2D menu, select Optimetrics
Analysis > Add Screening &
Optimization.
- Under the Goals tab, select the optimizer by selecting Sequential Nonlinear Programming(Gradient) from the Optimizer drop-down menu.
- Type the maximum number of iterations you want Optimetrics to perform during the optimization analysis in the Max. No. of Iterations text box.
- Under Cost Function, add a cost function by selecting the Setup Calculations button to open the Add/Edit Calculation dialog.
- If you want to select a Cost Function Norm Type:
- Check the Show Advanced Option check box.
- Select L1, L2, or Maximum.
- Optionally, click the button for setting HPC and Analysis Options, which allows you to select or create an analysis configuration.
- In the Variables tab, specify the Min/Max values for variables included in the optimization, and the Min/Max Focus for the analysis.
- You may also override the variable starting values by clicking the Override checkbox and entering the desired value in the Starting Value field.
- Optionally, modify the values of fixed variables that are not being optimized.
- Optionally, set Linear constraints.
- Select the View all columns check box to see all columns, including hidden columns.
- In the General tab, specify whether Optimetrics should use the results of a previous Parametric analysis or perform one as part of the optimization process.
- Under the Options
tab, if you want to save the field solution data for every solved design
variations in the optimization analysis, select Save
Fields And Mesh.
Note: Do not select this option when requesting a large number of iterations as the data generated will be very large and the system may become slow due to the large I/O requirements.
The Setup Optimization dialog box appears.
The Cost Function Norm Type drop-down menu appears.
A norm is a function that assigns a positive value to the cost function.
For L1 norm the actual cost function uses the sum of absolute weighted values of the individual goal errors. For L2 norm (the default) the actual cost function uses the weighted sum of squared values of the individual goal error. For the Maximum norm the cost function uses the maximum among all the weighted goal errors. (For further details, see Explanation of the L1, L2, and Max Norms in Optimization.)
The norm type doesn’t impact goal setting that use as condition the “minimize” or “maximize” scenarios.
Enabling the Update design parameters’ value after optimization check box will cause Optimetrics to modify the variable values in the nominal design to match the final values from the optimization analysis.
You may also select Copy geometrically equivalent meshes to reuse the mesh when geometry changes are not required, for example when optimizing on a material property or source excitation. This will provide some speed improvement in the overall optimization process.