Some Models for Multiple Attribute Decision Making with Intuitionistic Fuzzy Information and Uncertain Weights

Multiple attribute decision making problems with uncertain weights in intuitionistic fuzzy setting are investigated. Some concepts related to the theory of intuitionistic fuzzy set (IFS), including intuitionistic fuzzy weighted averaging (IFWA) operator, score function, and accuracy function, are reviewed. Based on the technology for order preference by similarity to idea solution (TOPSIS) method and the score matrix converted from decision matrix given in the form of intuitionistic fuzzy number (IFN), some quadratic programming models, by which the attribute weights can be derived, are established. Then, the alternatives are ranked, and the most desirable one is selected according to the score and accuracy degree of the collective IFN aggregated by IFWA operator. Finally, an example about evaluation of teaching was discussed to verify the effectiveness of the proposed approach.