Configuring the Hooke-Jeeves Technique

Select the optimization technique as described in Configuring the Technique and Execution Options.

In the Optimization Technique Options area, enter the following:

Option	Description
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` $> 1$ .
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 difference between the upper and lower bound of the parameter. (i.e., if a design variable has a starting value of 1.0 with upper and lower bounds of 10 and -10, respectively, and the Relative Step Size is 0.02, the initial perturbation will be 0.02 x 20=0.4). Isight determines the subsequent Relative Step Size based on a computation related to the design space size. However, if the upper or lower bound is not mentioned, the initial step size during the design perturbations is determined as a fraction of the parameter value (i.e., if a design variable has only a starting value of 1.0 and the Relative Step Size is 0.02, the initial perturbation will be 0.02 x 1.0=0.02). The initial perturbation is set to the Relative Step Size if the starting value of design variable is 0.
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., $1 \times 10^{- 4}$ ) have a quicker running time but a less accurate estimate of the optimum. Smaller Termination Step Size values (e.g., $1 \times 10^{- 7}$ ) have a longer running time but a more accurate estimate of the optimum. The default value is $1 \times 10^{- 6}$ .
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: $P e n a l t y = P e n a l t y B a s e + P e n a l t y M u l t i p l i e r \times S u m ({V i o l a t i o n}_{i} \times W_{i} / S_{i}) \land P e n a l t y E x p o n e n t$ where ${V i o l a t i o n}_{i}$ is the $i - t h$ constraint violation value, $W_{i}$ is the corresponding weight factor, and $S_{i}$ 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 $1 \times 10^{30}$ .
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 $1 \times 10^{30}$ .

Click Update Component to save your changes.