Modeling Dependence and Feedback among Criteria with Decision

Decision Adviser – a decision support tool for the evaluation of criteria weights by HEFCM method
Decision Adviser (DA) is a software realization of the HEFCM method. DA is Microsoft Excel Add-in
and it works with all current versions of Microsoft Excel from version 97. It can be downloaded from
http://www.opf.slu.cz/kmme/da/, and it consists of four individual files:
•
DA.xla – main module with user interface written in Visual Basic for Applications,
•
DA.dll – it contains special functions used by the application, it is written in C#,
•
DA.xll – it contains library for linking C# modules with Excel called Excel-DNA
(http://exceldna.codeplex.com),
•
DA.dna – configuration file for Excel-DNA module.
All four files must be placed in the same folder and macros must be permitted before running the
module (see Excel documentation for details). DA itself can be executed by double clicking on the file
DA.xla. After executing the add-in there will appear a new menu item “DA” in the Add-ins ribbon (in
older Excel versions the menu item “DA” will appear in the top level menu). A new decision problem
can be generated by clicking on “New problem” item in the main DA menu, see figure 8.
Figure 8. New problem menu
Then there will be shown a form with main problem characteristics, see figure 9.
Figure 9. New problem characteristics
In the form there are following basic settings: the number of criteria and the number of variants
(alternatives). When the form is submitted a new sheet is generated. First, the names of criteria and
variants are set, see figure 10.
Figure 10. Names of criteria and variants
Next step is comparison of individual criteria using pairwise comparison matrix with elements
saying how much more important is criterion in the row than the criterion in the column. In the
pairwise comparison matrix users enter values only in the upper triangle. The values in the lower
triangle are reciprocal and automatically calculated. In the very right column there are calculated
weights of individual criteria w, see figure 11.
Figure 11. Criteria comparison
Following step is expressing dependency among individual criteria using pairwise comparison
matrix. In the very right column there is automatically calculated vector of weights m, see figure 12.
Figure 12. Criteria dependency
The final step is the evaluation of variants according to individual criteria, see figure 13.
Figure 13. Evaluation of variants
In the top right matrix are calculated weights W32 of all variants (rows) according to individual
criteria (columns). At this stage synthesis is automatically performed and the final weights of variants
are shown in figure 14 and graphical representation is provided in figure 15. A comparison with
AHP/ANP can be performed via ExpertChoice/SuperDecisions or another free Microsoft Excel add-in
presented in Perzina and Ramik (2012).
Figure 14. The final weights of variants (alternatives)
Figure 15. A graphical comparison of the final weights of variants (alternatives)