In this paper we first highlight what we consider a drawback of most consistency indices for pairwise comparison matrices. In our opinion they do not take into account whether the elicited judgements are close to indifference or, on the contrary, they express strong preferences in comparing the alternatives, with the result that the latter case is unfairly penalized. We then introduce a consistency preserving transformation. By means of this transformation we define an equivalence relation in the set of pairwise comparison matrices and propose a new method for a more fair evaluation of the consistency. Finally, we extend the new method to fuzzy preference relations. © Springer-Verlag Berlin Heidelberg 2007.
Fair consistency evaluation in fuzzy preference relations and in AHP / Brunelli, M., Fedrizzi, M.. - STAMPA. - 4693:2(2007), pp. 612-618. (11th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2007, and 17th Italian Workshop on Neural Networks, WIRN 2007 2007) [10.1007/978-3-540-74827-4_77].
Fair consistency evaluation in fuzzy preference relations and in AHP
Brunelli, Matteo;Fedrizzi, Michele
2007-01-01
Abstract
In this paper we first highlight what we consider a drawback of most consistency indices for pairwise comparison matrices. In our opinion they do not take into account whether the elicited judgements are close to indifference or, on the contrary, they express strong preferences in comparing the alternatives, with the result that the latter case is unfairly penalized. We then introduce a consistency preserving transformation. By means of this transformation we define an equivalence relation in the set of pairwise comparison matrices and propose a new method for a more fair evaluation of the consistency. Finally, we extend the new method to fuzzy preference relations. © Springer-Verlag Berlin Heidelberg 2007.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione
