Analytic Hierarchy Process Based on the Magnitude of Z-Numbers

Abstract

The analytic hierarchy process (AHP) is a powerful multi-criteria and multi-alternative decision-making model which helps decision makers in giving preferences using pairwise comparison matrices. The development of AHP using fuzzy numbers got attention from many researchers due to the capability of fuzzy numbers in handling vagueness and uncertainty. The integration of AHP with fuzzy Z-numbers has improved the model since the reliability of decision makers is considered, in which the judgement is followed by the degree of certainty or sureness. Most of the existing decision-making models based on Znumbers transform the Z-numbers into regular fuzzy numbers by integrating the reliability parts into the restriction parts which has caused a great loss of information. Hence, this research develops the AHP based on the magnitude of Z-numbers, in which the magnitude is used to represent the criteria weights. A numerical example of criteria ranking for the prioritization of public services for digitalization is implemented to illustrate the proposed AHP model.