TY - GEN
T1 - Fuzzy Multi-Criteria Selection of Non-Ferrous Scrap Metal Suppliers
AU - Yeh, Chung Hsing
AU - Kuo, Yu Liang
N1 - Funding Information:
ACKNOWLEDGMENT This research was supported by an Innovation Connections grant funded by the Department of Industry, Science, Energy and Resources, Australian Government.
Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/11
Y1 - 2020/10/11
N2 - Selecting non-ferrous scrap metal suppliers involves evaluating each supplier and its available scrap metals in terms of quantitative and qualitative criteria in each selection round. This paper presents a new approach for developing and selecting fuzzy multi-criteria decision making (MCDM) methods to address the non-ferrous scrap metal supplier selection problem with fuzzy data. The approach develops different fuzzy MCDM methods by combining three normalization processes and three aggregation processes commonly used in MCDM research. In particular, a specific defuzzification process is used to reflect the decision maker's risk attitude about the current global commodity market. A validation procedure using fuzzy c-means clustering is applied to select among inconsistent ranking results produced by different fuzzy MCDM methods. An empirical study on a non-ferrous scrap metal company in China is conducted to illustrate how fuzzy MCDM methods are developed and selected.
AB - Selecting non-ferrous scrap metal suppliers involves evaluating each supplier and its available scrap metals in terms of quantitative and qualitative criteria in each selection round. This paper presents a new approach for developing and selecting fuzzy multi-criteria decision making (MCDM) methods to address the non-ferrous scrap metal supplier selection problem with fuzzy data. The approach develops different fuzzy MCDM methods by combining three normalization processes and three aggregation processes commonly used in MCDM research. In particular, a specific defuzzification process is used to reflect the decision maker's risk attitude about the current global commodity market. A validation procedure using fuzzy c-means clustering is applied to select among inconsistent ranking results produced by different fuzzy MCDM methods. An empirical study on a non-ferrous scrap metal company in China is conducted to illustrate how fuzzy MCDM methods are developed and selected.
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U2 - 10.1109/SMC42975.2020.9283322
DO - 10.1109/SMC42975.2020.9283322
M3 - Conference contribution
AN - SCOPUS:85098844840
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 841
EP - 847
BT - 2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020
Y2 - 11 October 2020 through 14 October 2020
ER -