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EN
Deriving true priority vectors from intuitive pairwise comparison matrices constitutes a key part of the Analytic Hierarchy Process. The Eigenvalue Method, commonly applied in the Analytic Hierarchy Process, is the most popular concept in the process of ratio scaling. It is known that the Eigenvalue Method captures transitivity in matrices that are not consistent in a unique way. However, there are other methods such as statistical estimation techniques and methods based on constrained optimisation models that are equally interesting. This article compares two novel methods for priority vectors deriving, which combine the eigenvalue concept with a constrained optimisation based approach. Evidence is provided that contrary to the logarithmic least squares method, they coincide with the Eigenvalue Method in capturing the ratio scale rank order inherent in inconsistent pairwise comparison judgments.
EN
There is a theory which meets a prescription of the efficient and effective multicriteria decision making support system called the Analytic Hierarchy Process (AHP). It seems to be the most widely used approach in the world today, as well as the most validated methodology for decision making. The consistency measurement of human judgments appears to be the crucial problem in this concept. This research paper redefines the idea of the triad’s consistency within the pairwise comparison matrix (PCM) and proposes a few seminal indices for PCM consistency measurement. The quality of new propositions is then studied with application of computer simulations coded and run in Wolfram Mathematica 9.0.
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