Ideal-Point Based Approach to Multiple Attribute Decision Making with Linguistic Evaluation

This paper focuses on the multiple attribute decision making problems with the attribute values being linguistic evaluations. The decision matrix is normalized by calculating the relative distance between the linguistic attribute values and their corresponding negative ideal one. Furthermore, 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, based on which the alternatives are ranked. An example is used to illustrate the proposed approach, which is suitable for extensive applications in the end.