English

Abstract

  Providing unique answers for any multicriteria decision making support methodology seems to be a crucial issue not only from the perspective of its creditability but also the entire concept validity. However, it is known that the analytic hierarchy process (AHP), as the prioritization and choice theory, can provide different priority vectors, depending on the method applied during the realization of the process. It is also the fact that we are being convinced from the very long time that only one approach in this matter is the only one and no other qualifies (principal right eigenvector method). However, this approach finds itself to have serious drawbacks and some flaws. This paper reveals some fundamental discoveries within this field thanks to seminal computer simulations for the entire AHP framework (as opposed to single matrix simulation research). The result concurs with the opinion that the right eigenvector method is not unique as long as reciprocal pairwise comparison matrices are concerned (what is embedded in the AHP process) and when it could be (nonreciprocal cases) it is not able to due to lack of inconsistency measure, which is an indispensable element of the entire AHP concept.   Key words: Decisions making support methodology, analytic hierarchy process, principal right eigenvector, priority vector, constrained optimization.