A Method for Multiple Attribute Decision Making with Incomplete Weight Information in Triangular Fuzzy Setting

The method for multiple attribute decision making with triangular fuzzy numbers is developed, in which the information about attribute weights is partly known. A fuzzy distance for triangular fuzzy numbers is introduced to measure difference between two alternatives. Based on the synthesis closeness degree, an optimization model by which the attribute weights can be determined is established. We utilize the TOPSIS method to aggregate the fuzzy information corresponding to each alternative, and then rank the alternatives according to their relative closeness. Finally, an illustrative example is given to demonstrate the proposed approach practicality and effectiveness.