A correlation based Intuitionistic fuzzy TOPSIS method on supplier selection problem

Supplier selection is a process in which one supplier is selected out of given suppliers on the basis of certain features such as reliability, maintenance, delivery performance, quality etc. Nowadays, supplier selection problem is a big issue because selection of the best supplier is a multi-criteria decision making (MCDM) problem under many combating criteria. The knowledge of the decision makers (DMs) is incomplete as well as imprecise. To deal this complex situation (uncertainty and hesitation), Intuitionistic fuzzy sets (IFSs) are used to select better DMs preferences. IFS is a powerful tool as it deals with membership function, non-membership function together with hesitancy. In this paper, we propose an intuitionistic fuzzy TOPSIS decision making method using correlation coefficient to deal with MCDM problems using IFS. Intuitionistic fuzzy weighted averaging (IFWA) operator is used to aggregate each DMs opinions for valuating the importance of alternatives and criteria. The proposed method is implemented on the numerical example given in F. E. Boran, S. Genc, M. Kurt and D. Akay, [Expert Systems with Applications, 8(2009), 11 363-11 368] to demonstrate about our procedure. The results obtained by our method matches with the results of Boran. Hence, our logic is proper for handling supplier selection problem.