A New Fuzzy Hierarchical Analysis Method Based on the Ideal Alternative

This paper puts forward a new fuzzy hierarchical analysis method, to extend the traditional AHP to fuzzy multi-attribute decision making environments. By substituting the fuzzy comparison vector for the crisp comparison matrix, our method is computationally easier, since there is no need to compute the eigenvalues or the eigenvectors, nor is there need to check the consistency of the comparison matrix. This method also uses an ideal alternative as the benchmark, thus successfully removing the dependence of alternative´s normalized priority weights on one another. Further, by using the differences between fuzzy numbers, based on the decision makers´ uncertainty preference, as the final priority indexes of alternatives, our method is more likely to achieve ranking results that are in more agreement with the decision makers´ intentions.