Inducing linguistic weights for type-1 OWA operators in soft decision making

Type-1 OWA operators provide an efficient way of aggregating linguistic opinions in the form of type-1 fuzzy sets for decision-makers. Like in Yager’s OWA operations, the identification of an appropriate type-1 OWA operator, i.e., to determine the linguistic weights in the form of type-1 fuzzy sets, is crucial in type-1 OWA based aggregation. Indeed, these weights reflect the decision-makers’ desired agenda for aggregating the preferences or criteria. In this paper, for the sake of identifying linguistic weights used in the type-1 OWA operators, type-2 linguistic quantifiers are proposed, in which the higher level of uncertainty of linguistic quantifiers is modelled by type-2 fuzzy sets. Some examples are provided to illustrate the proposed concepts.