Some aggregation operators with intuitionistic trapezoid fuzzy linguistic information and their applications to multi-attribute group decision making

We study the multi-attribute group decision making (MAGDM) problems in which the attribute values provided by the decision makers take the form of intuitionistic trapezoid fuzzy linguistic (ITrFL) information considering the uncertainty and inaccuracy of input arguments. Some new aggregation operators called intuitionistic trapezoid fuzzy linguistic weighted average (ITrFLWA), intuitionistic trapezoid fuzzy linguistic ordered weighted average (ITrFLOWA) and intuitionistic trapezoid fuzzy linguistic hybrid weighted average (ITrFLHWA) operators are proposed at first. Then, we study some desirable properties of the proposed operators, such as monotonicity, idempotency, commutativity and boundedness. Next, two novel approaches based on the proposed operators are developed to solve MAGDM problems with intuitionistic trapezoid fuzzy linguistic information. Finally, an illustrative example of emergency logistics supplier selection is provided to verify the feasibility of the proposed approaches.