Multiple Attribute Decision Making Based on Fuzzy Selected Subset and Linguistic Variables

This paper focuses on the multiple attribute decision making problems with the attribute values being numeric, uncertain fuzzy selected subset and linguistics variable evaluations. For the fuzzy selected subset attribute values, by calculating the fuzzy preference relation between them and the quantifier guided dominance degrees of them can be obtained as their single-point evaluations. For the linguistics variable attribute values, by calculating the relative distance between the alternatives and their corresponding negative ideal points, their crisp values of evaluation are obtained. Thus, the hybrid decision matrix is normalized into a single-point one, based on which a mathematical programming model is set up to figure out the attribute weights with the overall values of the alternative being the goals. In addition, the overall values of the alternatives are obtained for ranking the alternatives. An example is used to illustrate the proposed approach, which is suitable for extensive applications in the end.