Tips and Tricks

• Only one objective parameter can be optimized at a time f(x).
• Continuity in parameter value is required. Multiple discrete value parameters cannot be used as free parameters.
• Using a parameter which is constrained by a relation as a free parameter may lead to unpredictable results.
• For the gradient based algorithm (local search) put at least three times the number of free parameters as number of updates without improvement.
• If you want to modify free parameters driven by an Equivalent Dimension feature, select the Value parameter located below the Equivalent Dimension feature. Note that you will not be able to directly apply ranges and steps to the parameters making up the Equivalent Dimension: Only the Value parameter located below the Equivalent Dimension feature can be applied ranges and steps. Therefore, if you apply ranges and/or steps to the Value parameter, the parameters making up the equivalent dimension will have the same ranges or/and steps as the Value parameter.
• For gradient based algorithms (derivative provider excepted), the gradients are calculated by finite difference. This is one of the causes of imprecision. A second cause of imprecision comes from measures that are provided by various CATIA applications. Optimization results precision depends on the 2 previous causes.