Configuring the Multifunction Optimization System Tool (MOST) 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
Max 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.
Convergence Epsilon	This parameter sets the convergence criterion for MOST. If the necessary Kuhn-Tucker optimality conditions are satisfied to within Convergence Epsilon, optimization is terminated. The default value is $1 \times 10^{- 4}$ .
Rel Step Size	This parameter sets the relative finite difference step size for the creation of the linear model. The value type is real. The default value is $1 \times 10^{- 4}$ . Other possible values are $> 0.0$ .
Min Abs Step Size	This parameter sets the minimum absolute finite difference step for the creation of the linear model. The value type is real. The default value is $1 \times 10^{- 4}$ . Other possible values are $> 0.0$ .
Max Confirmation Runs	This parameter specifies the number of iterations that must satisfy the objective convergence criterion before optimization terminates. The default is 5.
Acceptable Obj Change	This parameter specifies the acceptable value for objective change for optimization termination. The default is $1 \times 10^{- 10}$ .
Constraint Tolerance	This parameter specifies the acceptable constraint violation for feasible designs. The default is $1 \times 10^{- 4}$ . Other possible values are $> 0$ .
Max 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 otimization 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.