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Article type: Research Article
Authors: Zhang, Huan*
Affiliations: School of Economics and Management, Southeast University, Nanjing, Jiangsu, China
Correspondence: [*] Corresponding author. Huan Zhang, School of Economics and Management, Southeast University, Nanjing, Jiangsu 211189, China. Tel./Fax: +86 13770963769; E-mail: [email protected].
Abstract: Along with the development of human being, the environmental problems have attracted more and more attention, “The Green” will become the main trend in the 21th century, and “The Green Action” will be an important department and a decisive factor to any country and enterprise which take part in the competition of the world market. Based on the above analysis, it is an important mode for the modern enterprise. We propose “The Green Idea” to the management of supply system, and then construct “The Green Supply Management” to reduce the resource cost and the environmental affect. In the study of “The Green Supply”, how to estimate the performance with high accuracy is of great importance. Furthermore, high quality performance evaluation may let the enterprise to answer the questions, to discover the solutions, and then to enhance the quality of the operation and improvement of “The Green Supply”. Therefore, it is very crucial to enhance “The Green Supply” by making the performance evaluation with high accuracy. In this paper, we study on the multiple attribute decision making problems to estimate the performance in green supply chain based on environmental economics with fuzzy information. Then, we have developed the fuzzy Hamacher correlated averaging (FHCA) operator. We have exploited the FHCA operator to multiple attribute decision making to estimate the wireless network security with fuzzy information. In the end, an example to estimate the performance in green supply chain based on environmental economics has been proposed to prove the effectiveness of the proposed approach.
Keywords: Multiple attribute decision making, triangular fuzzy number, performance in green supply chain, environmental economics
DOI: 10.3233/JIFS-16576
Journal: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 3, pp. 2625-2631, 2017
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