A new three-way multi-criteria decision-making method with fuzzy complementary preference relations based on additive consistency

The optimal selection, ranking and classification of objects are important aspects in the multi-criteria decision-making (MCDM) problem. In this paper, we try to propose a three-way MCDM method with fuzzy complementary preference relation based on additive consistency to select the optimal object, rank objects and classify objects at the same time, which will help decision-makers better make decisions. Firstly, we give the fuzzy complementary judgment matrix based on additive consistency. Then, based on this matrix, we construct the concept of -similarity class, and define a new relative loss function. Subsequently, we describe the detailed decision-making processes of the newly proposed three-way MCDM method. Further, through the trainer selection problem, we verify the feasibility of the method. Comparative analyses show that our method has stronger decision-making function than some existing methods. Experimental analyses show that our method is stable in ranking the considered objects and selecting the optimal object. Moreover, the proposed method can not only provide reasonable ranking decision suggestion for decision-makers, but also can meet the decision-makers' preference in the classification decision. (C) 2022 Elsevier Inc. All rights reserved.

Automated summary

This paper proposes a three-way multi-criteria decision-making method based on fuzzy complementary preference relation, which can select the optimal object, rank objects, and classify objects at the same time, providing better decision support for decision-makers.