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Evaluate

Evaluate

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Evaluate

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In the Evaluate step, approaches are executed and monitored. In a DOE, Fit, or Stochastic approach, the Evaluate step consists of the following tabs:

•Evaluation Tasks
•Evaluation Data
•Evaluation Plot

 

In an Optimization approach, the Evaluate step, has two additional tabs:

hmtoggle_plus1greyIteration History

In the Iteration History tab, a report is generated for iterations only; whereas in the Evaluation tab, a report is generated for all of the runs.

In comparison to the Evaluation tab, the Iteration History tab displays four additional columns that are present in all optimization studies.

Column

Description

Step Index

Corresponds to the row number in the Evaluation table.

Step Major

Displays the iteration number where the current optimal is found at.

Violation Code

Displays one of three different numbers: 0 (design is feasible), 1 (design is near violated), and 2 (design is violated).

You can visualize the violation codes in the following plot, which displays a minimized objective versus an output response constrained to stay below a bound. Design A has violation code 0, design B has a violation code of 2, and design C has a violation code of 1. The plot exaggerates the size of the green zone for visualization, it is typically very small.

violation_diagram

Optimal Step Major

Filled only after the approach evaluation is completed, displays the Step Major where it is found

 

The Iteration History table also uses color coding to help you determine which designs are feasible, optimal, and violated. The following combinations of color coding are available:

•White Background/Black Font

feasible design.
•White Background/Red Font

violated design.
•White Background/Orange Font

acceptable design, but at least one constraint is near violated.
•Green Background/White Font

optimal design.
•Green Background/Orange Font

optimal design, but at least one constraint is near violated.
Note:If an iteration contains a violated constraint, the violated constraint is displayed in a bold font.

iterationhistorycolorcoding

Additional columns are added to the Iteration History table if the objective of your study is system identification or if you are using one of the probabilistic methods.

If your objective function is System Identification; the following columns will be added to the Iteration History table:

•Objective Function Value

displays the sum of normalized difference-squared between the objective function value and target value.
•DTV

displays the delta between the target value and the objective value for each objective.
•DTVN

displays the normalized DTV for each objective.

hs_001

If you are using SORA or SORA_ARSM, a Percentile Value (PV) column will be added to the Iteration History table for each constraint. The PV column displays the value of the constraint that meets the required reliability. Consider a case where a constraint value needs to be less than 75.0 with 98% reliability (constraint 2 below). In the first iteration, SORA finds a design with a constraint value of 75.025, but the PV value for 98% reliability is at 99.383. Hence, this design meets the constraint's upper bound, but does not meet the reliability requirement. In the sixth iteration, SORA finds a design with a constraint value of 57.412 and the PV value for 98% reliability is at 75.075. This design meets the reliability constraint, as 98% of the design will have a constraint value less than 75.075.

pvcolumn

Note:If you turn on the robust optimization for SORA and SORA_ARSM, you will also see that a PV column has been added to the Iteration History table for the objective function.

 
hmtoggle_plus1greyIteration Plot

In the Iteration Plot tab, you can plot the iteration history of a study's objectives, constraints, input variables and unused output responses. When the objective history is plotted, infeasible designs are marked with larger markers.

iterationplot2d1

When the constraint history is plotted, the constraint bounds can be marked with a datum line. To activate this feature, click on the Color Wheel and select Bounds.

iterationplot2d

 

 

While the evaluation is in progress, it is possible to:

•Switch from one tab to another.
•Stop the process by clicking hs_stop.

 

 

See Also:

Tabs