A new approach for multicriteria group decision making under interval type-2 fuzzy environment

Abstract

The multicriteria group decision-making method in fuzzy environment has become the focus of many scholars. The purpose of this paper is to extend the traditional ORESTE (organísation, rangement et Synthèse de données relarionnelles) method to solve the multi-criteria group decision-making problem under IT2FS environment. The main contributions of this paper are to define a new similarity measure and a global preference score function based on the new similarity measure. First, a new similarity measure of two IT2FSs is defined. Then, some properties of the new similarity measure are investigated, and a comparison between the new similarity measure and other existing similarity measures is provided. Subsequently, a global preference score function is defined based on the new similarity measure. The average preference score is derived using the power average operator, and the weak order of the alternatives is obtained according to the average preference score. Furthermore, a PIR (P: preference; I: indifference; R: incomparability) structure is constructed to reach a strong ordering of alternatives. Finally, the feasibility and effectiveness of the proposed method is illustrated by a practical case of selecting the best supplier involving comparisons with the ELECTRE-based outranking method and IT2FS-TOPSIS method. And the new approach proposed in this paper can be applied to e-commerce, medical decision making, product recommendation, and fault diagnosis.