Robustness threshold methodology for multicriteria based ranking using imprecise data

It is well established that making decisions from defined data according to various criteria requires the use of MultiCriteria Decision Aiding or Analysis (MCDA) methods. However the necessary input data for these approaches are often ill-known especially when the data are a priori estimated. The common MCDA approaches consider these data as singular/scalar values. This paper deals with the consideration of more realistic, values by studying the impact of imprecision on a classical “precise” ranking established with ACUTA, a method based on additive utilities. We propose a generic approach to establish the concordance of pairwise relations of preference despite interval-based imprecision by complementing ACUTA with a computation of Kendall's index of concordance and of a threshold for maintaining this concordance. The methodology is applied to an industrial case subjected to Sustainable Development problems.