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.