TWO-SIDED MATCHING DECISION WITH TRAPEZOIDAL INTUITIONISTIC FUZZY NUMBERS USING SIMILARITY MEASURES

In the paper, we propose one novel method for handling two-sided matching problems with trapezoidal intuitionistic fuzzy numbers (TrIFNs) based on similarity measures between TrIFNs. First, we present the two-sided matching problem based on TrIFNs. Then, the matching model with TrIFNs is built. For model solution, we propose one similarity measure for calculating the degree of similarity among TrIFNs. The presented similarity measure between TrIFNs is combined with two similarity measures between generalized trapezoidal fuzzy numbers (GTrFNs), where maximum membership degrees, minimum non-membership degrees, areas, perimeters are used to calculate it. Using the similarity measures between TrIFNs, the matching model with TrIFNs can be converted into that with similarity measures. By using the arithmetic mean method, normalization formulas and the linear weighting method, the matching model with similarity measures is changed to a mono-goal model. The optimum matching scheme is got through solving the model. In the end, the effectiveness of the developed method can be expounded using one matching example.