Configuring the Hooke-Jeeves Technique

The Hooke-Jeeves technique begins with a starting guess and searches for a local minimum.

See Also
Hooke-Jeeves Direct Search Method Technique
Configuring the Technique and the Execution Options
  1. From the Flow section of the action bar, click Optimization and drop it on the process diagram.
  2. Double-click Optimization .
    The Optimization Editor appears.
  3. From the General tab's Optimization Technique list, select Hooke-Jeeves.

  4. In the Optimization Technique Options area, enter or select the following:
    OptionDescription
    Probe Count Extend 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, Process Composer 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 The maximum number of e valuations. The default is 100.
    Relative Step Size The initial step size during the design perturbations as a fraction of the parameter value (that is, 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). Process Composer determines the subsequent Relative Step Size based on a computation related to the design space size (for example, variable upper and lower bounds).
    Step Size Reduction Factor 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 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 (for example, 1 ⁢   ×   ⁢ 10 − 4 )) have a quicker running time but a less accurate estimate of the optimum. Smaller Termination Step Size values (for example, 1 ⁢   ×   ⁢ 10 − 7 ) have a longer running time but a more accurate estimate of the optimum. The default value is 1 ⁢   ×   ⁢ 10 − 6 .
    Penalty Base The 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 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 × ⁢ S u m ⁢ ( V i o l a t i o n i × W i / S i ) ∧ 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 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 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.
    Max Failed Runs 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 adapter will terminate execution. To disable this feature, set this option to any negative value (for example, –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 The value of the Penalty parameter that is used for all failed subflow runs. The default value is 1 ⁢   ×   ⁢ 10 30 .
    Failed Run Objective Value The value of the Objective parameter that is used for all failed subflow runs. The default value is 1 ⁢   ×   ⁢ 10 30 .
  5. Click Ok to save your changes and to close the Optimization Editor.