Probe Count |
Extends the standard Hooke-Jeeves process by allowing the design search to be performed
with more than one moving search point, or 'probe' running in parallel.
When you select Execute in parallel to enable parallel processing and
N probes are active, the SIMULIA Execution Engine dispatches a batch of N candidates for
new probe points on each iteration. Enabling parallel processing is effective only when Probe Count .
|
Max Evaluations |
This parameter sets the maximum number of evaluations. The default is
100. |
Relative Step Size |
This parameter determines the initial step size during the design perturbations
as a fraction of the parameter value (i.e., if a design variable has
a starting value of 1.0 and the Relative Step Size
is 0.02, the initial perturbation will be 0.02). Isight
determines the subsequent Relative Step Size based
on a computation related to the design space size (e.g., variable upper
and lower bounds). |
Step Size Reduction Factor |
This parameter sets the step size reduction factor. It must be set to
a value between 0.0 and 1.0. Larger values give greater probability of
convergence on highly nonlinear functions, at a cost of more function
evaluations. Smaller values reduce the number of evaluations (and the
program running time) but increase the risk of nonconvergence. The default
value is 0.5. |
Termination Step Size |
This parameter sets the termination step size. When the algorithm begins
to make less and less progress on each iteration, it checks this parameter.
If the step size is below the Termination Step Size,
the optimization terminates and returns the current best estimate of
the optimum. Larger Termination Step Size values
(e.g., ) have a quicker running time but a less accurate estimate
of the optimum. Smaller Termination Step Size
values (e.g., ) have a longer running time but a more accurate
estimate of the optimum. The default value is . |
Penalty Base |
Hooke-Jeeves algorithm evaluates the quality of a design point using
the combined value of the objective function and penalty function. When
calculating the penalty function of the design, the Penalty
Base option can be used for all designs that violate at least
one constraint. This allows the technique to better differentiate feasible
designs with a slightly higher objective function from infeasible designs
with a slightly lower objective function. The total penalty function is calculated as follows:
where is the constraint violation
value, is the corresponding weight factor,
and is the corresponding scale factor. The
penalty base is set to zero if no constraints
are violated. The default value is 0.0. |
Penalty Multiplier |
This parameter is used to increase or decrease the effect of the total
constraint violations on the measure of the design quality. The default
value is 1000.0. |
Penalty Exponent |
This parameter can be used to increase or decrease the nonlinearity
of the effect of the total constraint violations on the penalty function
value. The type of value is integer. The default value is 2. |
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 . |