A multiple attribute decision making threeway model for intuitionistic fuzzy numbers Abstract   In order to use threeway decision (TWD) to solve multiple attribute decision making (MADM) problems, in this article, a new TWD model with intuitionistic fuzzy numbers (IFNs) is proposed. First of all, we define the relative loss functions to demonstrate some features of loss functions in TWDs, which is the basis for future research. Then, based on the correlation between the loss functions and the IFNs, we get the relative loss functions based on IFNs. At the same time, the classification rules of the TWDs are discussed from different viewpoints, including the thresholds and their properties. Aiming at MADM problems with unreasonable values, a new integrated method of relative loss functions is established to obtain a fairer loss integration result of alternatives. In addition, considering that there are no decision attributes and only condition attributes in MADM, we use grey relational degree to calculate the condition probability. In the end, a novel TWD model is proposed to solve MADM problems with IFNs, and a practical example on selecting suppliers is used to demonstrate its effectiveness and practicability.

Intuitionistic fuzzy TOPSIS method based on CVPIFRS models: An application to biomedical problems Abstract   In order to obtain the weights of a set of criteria by means of realworld data, an effective method based on the coveringbased variable precision intuitionistic fuzzy rough set (CVPIFRS) models is presented. By combining the CVPIFRS models with the idea of TOPSIS, we propose a decisionmaking method to effectively settle the complex and changeable bone transplant selections, which is one of typical multiattribute decisionmaking (MADM) problems. The sensitivity analysis of the proposed method shows that the approach is highly flexible and can be applied to a wide range of environments by adjusting the values of the intuitionistic fuzzy (IF) variable precision, together with the choice of different IF logical operators. Through a comparison of the proposed method and some existing MADM methods, it is shown that our method is more effective in dealing with these complex and changeable bone transplant selections issues.