About Feasibility and Optimization Studies
Feasibility and optimization studies allow you to have the system compute dimension values that cause the model to satisfy certain user-specified constraints. To access a feasibility or optimization study, click
Analysis and then click the arrow next to
Feasibility/Optimization. Click
Feasibility/Optimization and select the type of study from the dialog box.
Optimization Study
With an optimization study, you can specify the goal function in addition to the parameters for a feasibility study.
For an optimization study, you define the following attributes:
• A set of dimensions to vary
• A range within which each dimension can vary
• A set of constraints that you want the design to satisfy
• A goal function to be optimized (maximized or minimized)—a goal function is created as the result of an analysis feature
For an optimization study, the system does the following actions:
• Looks for feasible solutions
• Out of feasible solutions, selects the solution that optimizes the goal function
Feasibility Study
For a feasibility study, you define the following attributes:
• A set of model dimensions to vary
• A range within which each dimension can vary
• A set of constraints that you want the design to satisfy
The analysis constraints are defined as equalities or inequalities that use parameters (which are the result of an analysis feature) and constant values. A sample constraint may appear as follows: length < 6.3 or distance = 11
For a feasibility study, the system performs the following actions:
• Attempts to find a set of dimension values within the specified ranges that satisfies all of the constraints.
• If a solution is found, changes the model display to show the dimensions modified to the new values.
You can either accept these new dimensions or undo the changes and revert the model to its state before the feasibility study. There can be many solutions in a feasibility study that satisfy all constraints. The system converges to one of the solutions.