A novel supplier selection method that integrates the intuitionistic fuzzy weighted averaging method and a soft set with imprecise data
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Along with advances in technology and the advent of the information age, supply chain competition will become the core strategy of enterprises that are in pursuit of a competitive advantage. Supplier selection and evaluation are key issues in the success of a competitive enterprise. Supplier selection for an enterprise is a typical multicriteria decision-making problem that includes qualitative and quantitative criteria. However, some input information can be missing or nonexistent in selecting suppliers, rendering it more difficult to choose the best supplier. To this end, the traditional supplier selection approach does not consider the ordered weights of the values of attributes, causing biased conclusions. Moreover, there is a significant amount of fuzzy and intuitionistic fuzzy information in real-world situations, for which the traditional approach in choosing the best supplier becomes no longer applicable. To solve these issues, this study proposes a novel supplier selection method, integrating the intuitionistic fuzzy weighted averaging method and the soft set with imprecise data, in identifying the best supplier in a supply chain. To illustrate our proposed method, a numerical example of the supplier selection problem is adopted. This paper also compares the results of the fuzzy weighted averaging, intuitionistic fuzzy weighted averaging, and intuitionistic fuzzy dependent aggregation operator methods in dealing with missing or nonexistent data. Based on our results, the proposed method is reasonable, effective, and better reflects real-world situations with regard to supplier selection.
KeywordsSupplier selection Intuitionistic fuzzy set Soft set Multi-criteria decision making Ordered weighted geometric averaging
The authors would like to thank the Ministry of Science and Technology, Taiwan, for financially supporting this research under Contract Nos. MOST 105-2410-H-145-002 and MOST 106-2410-H-145-001.
- Atanassov, K.T. (1983). Intuitionistic fuzzy sets. Central Tech Library, Bulgarian Academy Science, Sofia, Bulgaria. Report 1697/84.Google Scholar
- Mianabadi, H., Sheikhmohammady, M., Mostert, E., & Van de Giesen, N. (2014). Application of the ordered weighted averaging (OWA) method to the Caspian Sea conflict. Stochastic Environmental Research and Risk Assessment, 28(6), 1359–1372.Google Scholar
- O’Hagan, M. (1988). Aggregating template or rule antecedents in real time expert systems with fuzzy set logic. In Proceedings of the 22th Annual IEEE Asilomar Conference on Signals, Systems, Computers Pacific Grove, CA, USA, pp. 681-689.Google Scholar
- Wang, F., Zeng, S. L., & Zhang, C. H. (2013). A method based on intuitionistic fuzzy dependent aggregation operators for supplier selection, Mathematical Problems in Engineering. Article ID: 481202.Google Scholar
- Wang, X., Dang, Y. G., & Hou, D. Q. (2014). Multiattribute grey target decision method based on soft set theory. Mathematical Problems in Engineering. Article ID 307586.Google Scholar
- Wu, C. M., Hsieh, C. L., & Chang, K. L. (2013). A hybrid multiple criteria decision making model for supplier selection. Mathematical Problems in Engineering Article ID: 324283.Google Scholar