Managing Inconsistency With an Optimal Distribution of Information Granularity in Fuzzy Preference Relations

In decision-making with fuzzy preference relations, pairwise comparisons among all the attributes or alternatives in question are done by decision-makers to generate a matrix. The validity and reliability of the decision made is ensured if the consistency of this matrix is high, which usually requires alterations of the entries of the matrix. This research introduces a new consistency improvement procedure by allowing an information granularity level in the decision-making process. Concretely, to improve the consistency, it invokes a process of an optimal information granularity distribution across the related alterations of the entries of the matrix. To demonstrate its effectiveness, we complete some detailed experiments.