Reproducing Formula Results with AHP

Critics of the Analytic Hierarchy Process (AHP) often mislead themselves and others by constructing examples that they claim show the AHP draws false conclusions. The AHP has clear requirements for both the hierarchical structure and the priorities in the structure. It must be shown that any model that finds the AHP does not give correct results has first met these requirements. Problems must be correctly structured and priorities correctly set in the AHP model to get results that match expectations. The most common error is the belief that the AHP should be able to reproduce results in some magical way from some specific formula without including enough data in the model to truly represent the situation. Scientific formulas usually involve combinations of mathematical operations such as adding, multiplying, and raising factors to powers and they have been devised through a process of experimentation and adjustment to make predicted results fit observed outcomes. Remember those mysterious constants that crop up in some physics formulas? Figuring out what the constant has to be is usually based on a large number of experiments and that is part of the adjustment process. AHP models can reproduce the results of many formulas if one understands the principles of AHP well enough to set up the model so it properly incorporates known data. We examine a few of these examples and show how they should be properly modeled in this rebuttal paper that appeared in the Proceedings of the 2004 Multi Criteria Decision Making Conference.