Exploiting the type-1 OWA operator to fuse the ELICIT information

In a group decision making (GDM) problem, the information is fused to obtain a collective result, which helps to choose the best solution/s to the problem. Recently, a new representation model called Extended Comparative Linguistic Expressions with Symbolic Translation (ELICIT), which extends the representation of the comparative linguistic expressions (CLEs) to a continuous domain combining the advantages of the hesitant fuzzy linguistic term sets and 2-tuple linguistic representation model has been proposed to model experts' preferences. Due to the need of fusing experts' preferences in GDM processes, it is convenient to have enough flexible aggregation operators for such processes. However, so far, only two aggregation operators have been introduced to aggregate ELICIT information in GDM problems, the fuzzy arithmetic mean operator and the Bonferroni mean operator. Thus, it seems necessary to define new aggregation operators with different features to model wide range of decision-making scenarios. One widely used operator to aggregate preferences in decision making is the OWA operator. The key issue to apply the OWA operator is the reordering process of the arguments. However, the ELICIT information does not have an inherent order because it is represented by a fuzzy number. Therefore, the aim of this contribution is to define the type-1 ELICIT OWA operator by using crisp and fuzzy weights, particularly interval weights, and define a multi-criteria group decision making model which applies the type-1 ELICIT OWA operator to fuse the information. Additionally, an experimental study is introduced to demonstrate the feasibility of the proposed aggregation operator.