Abstract
Supplier selection plays an important role in supply chain system. In order to select the suitable suppliers, some methods of supplier selection have been studied extensively in fuzzy environment. In this paper, a fuzzy information fusion approach based on generalized fuzzy numbers (GFNs) is proposed to select the best supplier. Some aggregation operators with GFNs are also proposed. In addition, a new ranking formula based on mean values of GFNs is adopted to rank the suppliers. Finally, an empirical study of supplier selection is introduced to illustrate the proposed method. The results indicate that the proposed method could meet the different evaluation requirements of decision makers and offer an effective and practical way to select the best supplier.
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Acknowledgments
This research was supported in part by grants from the National Natural Science Foundation of China (#71222108, #71325001 and #71173028), Program for New Century Excellent Talents in University (#NCET-12-0086), the Research Fund for the Doctoral Program of Higher Education (#20120185110031) the Fundamental Research Funds for the Central Universities (ZYGX2015KYQD079).
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Li, G., Kou, G., Peng, Y. (2016). Fuzzy Information Fusion Approach for Supplier Selection. In: Cao, BY., Wang, PZ., Liu, ZL., Zhong, YB. (eds) International Conference on Oriental Thinking and Fuzzy Logic. Advances in Intelligent Systems and Computing, vol 443. Springer, Cham. https://doi.org/10.1007/978-3-319-30874-6_7
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DOI: https://doi.org/10.1007/978-3-319-30874-6_7
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