Similarity-based Fuzzy Inferior Ratio (FIR) variants for solving supplier selection problem

The Fuzzy Inferior Ratio (FIR) method has been acknowledged as one of the most beneficial approaches for the Multi-Criteria Decision Making (MCDM) in a fuzzy environment. It simultaneously uses a compromise solution that considers the distance of the alternatives with both Fuzzy Positive Ideal Solution (FPIS) and Fuzzy Negative Ideal Solution (FNIS). In this research, a method that integrates three different similarity measures (SMs) namely Similarity Measure 1, Similarity Measure 2 and Similarity Measure 3, into the Fuzzy Inferior Ratio (FIR) was proposed. The first SM using graded mean integration representation distance. Second SM using the center of gravity (COG) points and geometric distance. The third SM uses the geometric distance, the perimeter and the area of two trapezoidal fuzzy numbers. SM has the advantage since it uses different perspectives of fuzzy numbers other than geometric distance. It can be calculated by using other aspects such as area, perimeter and center of gravity of the fuzzy numbers. With the integration of SMs in FIR, the loss of information can be minimized. In this study, the proposed method that is FIR with different SMs is implemented to rank suppliers in the supply chain system. Then, the result is analyzed by comparing the ranking of the suppliers by using three different similarity measures. It is found that the results are consistent for all the variants of similarity-based FIR. The result of the three different SMs shows the same ranking and the best supplier to choose is Supplier 2.