CAGE User's Guide

Step 2: Create a CAGE Optimization Function

Any optimization algorithm you want to use in CAGE must be contained in an optimization function. A CAGE optimization function consists of two sections.

The first section defines the following attributes of the optimization:

• A name for the optimization
• A description of the optimization
• Number of objectives
• Labels for objective functions, so the user can match models in CAGE to the required algorithm objectives
• Number of constraints
• Labels for constraints, so the user can match models in CAGE to the required models in your algorithm constraints
• Number of operating point sets
• Labels for operating point sets, so the user can match data sets in CAGE to the required fixed variable data for your algorithm
• Any other parameters required by the optimization algorithm

The second section contains the optimization algorithm.

3. Open mbcOStemplate.m from the mbctraining directory.

1. You should see the following M-file in the MATLAB editor.

   

mbcOStemplate.m is an empty CAGE optimization function. The two (currently empty) sections of the function are labeled above. Note that this M-file can be used as a template for any optimization function that you write.

Creating an Optimization from Your Own Algorithm

Step 3: Define the Optimization Options