Ch. 9
Building Model-Driven Decision Support Systems

The Analytical Hierarchy Process technique (cf., Saaty, 1980; Saaty, 1990) can be characterized as a multi-criteria decision technique that can combine qualitative and quantitative factors in the overall evaluation of alternatives. This section provides a brief introduction to AHP with an emphasis on the general methodology.

The first step is to develop a hierarchical representation of a problem (see Figure 9.2). At the top of the hierarchy is the overall objective and the decision alternatives are at the bottom. Between the top and bottom levels are the relevant attributes of the decision problem, such as selection criteria. The number of levels in the hierarchy depends on the complexity of the problem and the decision-maker’s model of the problem hierarchy.

Next, in step 2 one needs to generate relational data for comparing the alternatives. This requires a decision-maker to make pairwise comparisons of elements at each level relative to the next higher level in the hierarchy. In the Analytical Hierarchy Process a relational scale of real numbers from 1 to 9 is used to assign preferences.

In Step 4, the priorities or weights of the lowest level alternatives relative to the top-most objective are determined and displayed. AHP facilitates a comprehensive and logical analysis of problems for which considerable uncertainty exists.