Interval Data Aggregation Technology for Large Scale Decision Making

In this paper, an improved multiple attribute decision making (MADM) method based on the proposed novel score function and accuracy function of interval-valued intuitionistic fuzzy numbers (IVIFNs) is proposed to aggregate large-scale data. The attribute values in the decision matrices provided by each decision-maker (DM), which are characterized by interval numbers. First, a transformation matrix is introduced to define the concepts of satisfactory set, un- satisfactory set and uncertainty set of alternatives. An approach is then developed for aggregating attribute values into IVIFNs, and we will obtain the collective evaluation of each alternative. Next, using the interval-valued intuitionistic fuzzy weighted averaging operator, the collective attribute values characterized by IVIFNs are aggregated to get the overall evaluation of alternatives. The score function and accuracy function are applied to calculate the score degree and the rank of each alternative. Finally, a large-scale example is given to verify the validity of the reported method.