An approach to deriving interval weights from interval fuzzy preference relations based on multiplicative transitivity
The derivation of priority weights plays an important role in multi criteria decision making (MCDM) with preference relations. In this paper, interval fuzzy numbers are used to capture vagueness and uncertainty in imprecise judgment data by means of interval fuzzy preference relations. The criterion weights or priority weights of decision alternatives are characterized by normalized interval weights. Based on multiplicative transitivity, a geometric least squares model is developed to derive interval weights from interval fuzzy preference relations. A geometric-least-squares-based approach is then put forward for solving MCDM problems with a hierarchical structure. An online shopping customer satisfaction evaluation problem is furnished to show the effectiveness and applicability of the proposed method.