FINANCING SELECTION METHOD IN DISCIPLINE EVALUATION USING A WEIGHTED INDUCED MODEL

The selection of a suitable financing alternative involves multifarious attributes that should be assessed to provide a basis foundation for decision-making. As an effective generation of intuitionistic fuzzy set and linguistic term, the intuitionistic linguistic set (ILS) has greater power for processing uncertain information during decision-making process. Keep this feature in mind, the main purpose of this paper is to investigate a weighted induced aggregation approach for decisionmaking problem concerning financing selection with complex uncertainty in term of intuitionistic linguistic (IL) information. For this, a new intuitionistic linguistic aggregation operator based on the weighted induced approach, namely the IL weighted induced ordered average-weighted averaging (ILWIOWAWA) operator, is proposed to integrate intuitionistic linguistic information. The special advantage of this operator is that it can integrate the subjective information with the particular attitudinal characters in form of order-induced variables in the same expression during information fusion. Moreover, it is able to deal with uncertain information represented by intuitionistic linguistic set very effectively. Some of its properties and particular cases are mathematically explored. We have proved that it has the properties of monotonicity, boundedness, idempotency, nonnegativity and reflexivity. A further extension of the proposed operator is also represented in term of quasiarithmetic means, then we get the quasi-arithmetic ILWIOWAWA (QILWIOWAWA) operator, which encompasses a very broad class of IL aggregation operators. In addition, based on the developer operator, a procedure for multiple attribute group decision-making (MAGDM) problems has been discussed. Finally, a numerical application related to the discipline evaluation in university is used to show the validity and practicability of the proposed method.