Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Article type: Research Article
Authors: Rao, Congjuna | Xiao, Xinpinga | Xie, Mingb | Goh, Markc | Zheng, Junjund; *
Affiliations: [a] School of Science, Wuhan University of Technology, Wuhan, P.R. China | [b] Department of Personnel, Handan College, Handan, P.R. China | [c] NUS Business School and The Logistics Institute Asia-Pacific, National University of Singapore, Singapore | [d] School of Economics and Management, Wuhan University, Wuhan, P.R. China
Correspondence: [*] Corresponding author. Junjun Zheng, School of Economics and Management, Wuhan University, Wuhan 430072, P.R. China. Tel./Fax: +86 02768753082; E-mail: jjzhengwhu@foxmail.com.
Abstract: Under the development mode of low carbon economy, selecting the best low carbon supplier is the basis and prerequisite for establishing low carbon supply chain, and is the inevitable choice to achieve sustainable development for enterprises. In this paper, we investigate the problem of low carbon supplier selection in the multi-source and multi-attribute procurement. Concretely, we establish a new evaluation index system of low carbon supplier selection based on cost, low carbon, quality and service capacity. Then we present a multi-attribute decision making method for low carbon supplier selection based on a linguistic 2-tuple VIKOR method. In this proposed decision method, the hybrid attribute values (the real numbers and linguistic fuzzy variables coexist) are transformed into linguistic 2-tuples, and a ranking method based on an extended VIKOR method is then presented to rank all alternative suppliers. We also give an application example to highlight the implementation, availability, and feasibility of the proposed decision making method.
Keywords: Low carbon economy, low carbon supplier selection, multi-attribute decision making, linguistic 2-tuple, extended VIKOR method
DOI: 10.3233/JIFS-151813
Journal: Journal of Intelligent & Fuzzy Systems, vol. 32, no. 6, pp. 4009-4022, 2017
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl