| Max Number of Iterations |
An iteration consists of two phases. In the first phase, a plausible
search direction is computed from the gradient of the objective function
and constraints at the current design point. In the second phase, new
designs are evaluated along the selected direction (cost: one run per
design) until no improvements are found or until a constraint is violated.
The two phases are repeated until the specified convergence requirements
are met. This option controls how many of these pairs of phases will
take place. The value type is integer. The default value is 40. |
| Relative Gradient Step |
This parameter sets the relative finite difference step size to be used
by the optimizer, when calculating gradients using finite difference
techniques. The default value is 0.01 (1%). |
| Min Abs Gradient Step |
This parameter sets the smallest (minimum) absolute value of the finite
difference step when calculating gradients. It prevents a step from being
too small when a parameter value is near zero. The default value is 0.001.
|
| Abs Convergence Criterion |
This parameter is a termination criterion. If the objective does not
change by more than this value in successive iterations, optimization
is terminated. The value type is real. The default value
is 0.001. |
| Rel Convergence Criterion |
This parameter is a termination criterion. If the fractional (relative)
change in objective value is smaller than the value of this criterion
for several successive iterations, the optimization is terminated. The
value type is real. The default value is 0.001 (0.1% of the objective
value). |
| Maximum Failed Runs |
This parameter is used to set the maximum number of failed subflow evaluations
that can be tolerated by the optimization technique. If the number of
failed runs exceeds this value, the optimization component will terminate
execution. To disable this feature, set this option to any negative value
(e.g., –1). When this option is set to a negative value, the optimization
will continue execution despite any number of failed subflow runs. |
| Failed Run Penalty Value |
This parameter represents the value of the Penalty
parameter that is used for all failed subflow runs. The default value
is . |
| Failed Run Objective Value |
This parameter represents the value of the Objective
parameter that is used for all failed subflow runs. The default value
is . |
| Save Technique Log |
Most optimization techniques create a log file of information/messages
as they run. This information can be useful for determining why an optimizer
took the path that it did or why it converged. Some of these log files
can get extremely large, so they are not stored with the run results
by default. Select this option if you want to store the log with the
run results (as a file parameter) for later viewing. |