Using the Gradient Based Algorithm to Optimize Problems With Non Satisfied Constraints 

This task explains how to use the Gradient based Algorithm to optimize Problems with non satisfied constraints.

  1. Open the KwoGettingStarted.CATPart file.

  2. From the Start > Knowledgeware menu, access the Product Engineering Optimizer workbench.

  3. Click the Optimize icon () to access the Optimization dialog box. The Optimization dialog box is displayed.

  4. Enter the parameters below in the Problem tab:

Optimization Type Target Value
Optimized Parameter Volume.1
Target Value 0.8L
Free Parameters
  xA yA xB yB
Inf. Range 40 40 50 40
Sup. Range 80 80 200 100
Algorithm Gradient Algorithm With Constraints
Termination Criteria
  • Maximum number of updates
  • Consecutive updates without improvements
  • Maximum Time (minutes)
  1. Enter the following constraints in the Constraints tab:

Constraint.1 Z**2 + Y**2 < 5000 mm2
Constraint.2 Y**2 + Z**2 > 1000 mm2
  1. Click Run optimization. The part looks like the one below after the optimization process is over:

  1. Redefine the ranges of the free parameters (see below):

Free Parameters
  1. Click Run optimization. The generated values are much closer to the Target value.

Click the graphic opposite to enlarge it.