Two Methods With Bidirectional Similarity for Optimal Selections of Supplier Portfolio and Supplier Substitute Based on TOPSIS and IFS

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Abstract

The optimal selections of supplier portfolios and supplier substitutes are important research contents of the supplier selection problem. However, most of the existing supplier selection methods are based on the efficiency of indicator capability of supplier, the complementary capability (i.e., weak similarity) between suppliers for the supplier portfolio, and the substitution capabilities (i.e., strong similarity) of supplier substitutes for the best supplier may not be considered. Therefore, two new supplier selection models, namely TOPSIS-NS considering the negative influence of similarity for supplier portfolio selection and TOPSIS-PS considering the positive influence of similarity for supplier substitute selection, are proposed based on TOPSIS and intuitionistic fuzzy set (IFS). Firstly, the efficiency of indicator capability of supplier is expressed by the membership degree of IFS obtained by TOPSIS, while the similarity among suppliers is expressed by the nonmembership degree of IFS obtained by the concordance correlation coefficient. Then, the process of TOPSIS-NS for supplier portfolio selection is constructed based on the score function of IFS, and the supplier portfolio selected by TOPSIS-NS can have higher complementary capabilities. Furthermore, the process of TOPSIS-PS for supplier substitute selection is constructed based on the accuracy function of IFS, and the supplier substitute selected by TOPSIS-PS can have higher substitution capabilities. Finally, two illustrative examples for optimal selections of supplier portfolio and supplier substitute are given respectively, and the results show the superiority of TOPSIS-NS in supplier portfolio selection and TOPSIS-PS in supplier substitute selection.

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Wang, C., Shi, J., Yang, Y., & Wang, R. (2024). Two Methods With Bidirectional Similarity for Optimal Selections of Supplier Portfolio and Supplier Substitute Based on TOPSIS and IFS. IEEE Access, 12, 1761–1773. https://doi.org/10.1109/ACCESS.2023.3348522

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