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- On the form page there are several fields that need to be filled out. For the Result Name field, specify something like As-Built MAUT. If you are using version 3.1.1 or earlier, then for the MAUT Results field select As-built Decision Attributes. Otherwise, you should see a field called Building Decision Support Attributes and you should select As-built Decision Attributes for that field.
- By default, the Risk Attitude is set to Risk Averse and the Variable Weights are User Defined. If you select MAEviz Calculated, then MAEviz will calculate the weights based converting the maximum values for each decision variable into dollar amounts and dividing by the total dollar amount for all variables. (e.g. (deaths x monetary-conversion) / (total dollars for all weights)). In the Advanced Parameters section, users can select a utility curve dataset. The default is eScience Sample Utility Functions, which were generated for an e-Science demonstration of MAEviz.
- After making the desired changes, click the Execute button.
- When the analysis has finished, there should be a new dataset with the name you provided in your scenario. If you right click on the dataset and select Show Attribute Table, you will see there is a new column called utility that has been added. This is the overall utility for the entire dataset. In our case, the utility is zero, which we could have guessed from looking at the utility functions and the results we had in our Building Decision Support Attributes dataset. The acceptable deaths limit was 30 and the acceptable injury limit was defined at 55, these numbers are well below what our expected death and injury totals, thus the very low utility score. The utility curves were defined for a small dataset and not intended for such a large dataset as ours.
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