Group decision making with linguistic information using a probability-based approach and OWA operators

Traditionally, decision-making problems that manage preferences from different experts follow a common resolution scheme composed of two phases: an aggregation phase that combines the individual preferences to obtain a collective preference value for each alternative; and an exploitation phase that orders the collective preferences according to a given criterion, to select the best alternative/s. In this paper, instead of using an aggregation operator to obtain a collective preference value, a random preference is defined for each alternative in the aggregation phase. To this end, a probability-based interpretation of weights is assumed. Then, the independent assumption imposed on alternatives allows us to work out probabilities of pairwise comparisons of random preferences. In order to obtain a raking order of alternatives for the exploitation phase, we define a choice function based on the ordered weight averaging (OWA) operator with help of the fuzzy majority.