Revisiting the approximated weight extraction methods in fuzzy analytic hierarchy process

摘要

There are simple approximated methods to extract the local weights from a pairwise comparison matrix which are row sums, inverse of column sums, arithmetic mean, and geometric mean. In this paper, first, we extend these methods to fuzzy analytic hierarchy process (FAHP) to extract the local weights as fuzzy numbers (FNs). Then, these weights are defuzzified using the center of gravity (COG) method. We also propose an approach to integrate different local weights obtained from different approximated methods to achieve a unified local weight. Moreover, this study proposes a novel and simple approach in which uncommon FNs are indirectly defuzzified based on COG method. This helps extend the multi-attribute decision-making methods to uncommon FNs. To illustrate the applicability of the proposed approaches, three numerical examples are given and their results are compared with some well-known FAHP methods in the literature.