An Extended TOPSIS Method for Multiple Attribute Decision Making based on Intuitionistic Uncertain Linguistic Variables

摘要

The intuitionistic uncertain linguistic variablescan easily express the fuzzy information in real world, andTOPSIS is a very effective decision making method and it hasbeen achieved more and more extensive applications. In thispaper, we will extend the TOPSIS method to deal with theintuitionistic uncertain linguistic information, and propose anextended TOPSIS method to solve the multiple attributedecision making problems in which the attribute values take theform of the intuitionistic uncertain linguistic variables andattribute weight is unknown. Firstly, the operational rules andproperties for the intuitionistic uncertain linguistic variablesare introduced. Then the distance between two intuitionisticuncertain linguistic variables is proposed and the attributeweight is calculated by the maximizing deviation method, andthe closeness coefficients to the ideal solution for eachalternative are used to rank the alternatives. Finally, anillustrative example is given to show the decision making stepsand the effectiveness of the proposed method.