  An overview of current debates and contemporary research devoted to the
modeling of decision making processes and their facilitation directs attention
to the Analytic Hierarchy Process (AHP). At the core of the AHP are various
prioritization procedures (PPs) and consistency measures (CMs) for a Pairwise
Comparison Matrix (PCM) which, in a sense, reflects preferences of decision
makers. Certainly, when judgments about these preferences are perfectly
consistent (cardinally transitive), all PPs coincide and the quality of the
priority ratios (PRs) estimation is exemplary. However, human judgments are
very rarely consistent, thus the quality of PRs estimation may significantly
vary. The scale of these variations depends on the applied PP and utilized CM
for a PCM. This is why it is important to find out which PPs and which CMs for
a PCM lead directly to an improvement of the PRs estimation accuracy. The main
goal of this research is realized through the properly designed, coded and
executed seminal and sophisticated simulation algorithms in Wolfram Mathematica
8.0. These research results convince that the embedded in the AHP and commonly
applied, both genuine PP and CM for PCM may significantly deteriorate the
quality of PRs estimation; however, solutions proposed in this paper can
significantly improve the methodology.
