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Journal of Applied Mathematics
Volume 2014, Article ID 767095, 12 pages
http://dx.doi.org/10.1155/2014/767095
Research Article

Applying Fuzzy Multiobjective Integrated Logistics Model to Green Supply Chain Problems

1Department of Industrial Engineering and Management, National Taipei University of Technology, No. 1, Section 3, Chung-Hsiao East Road, Taipei 10643, Taiwan
2College of Management, National Taipei University of Technology, No. 1, Section 3, Chung-Hsiao East Road, Taipei 10643, Taiwan
3Department of Transportation Science, National Taiwan Ocean University, Keelung City 202, Taiwan

Received 19 January 2014; Revised 12 June 2014; Accepted 13 June 2014; Published 7 July 2014

Academic Editor: Ricardo Perera

Copyright © 2014 Chui-Yu Chiu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The aim of this paper is attempting to explore the optimal way of supply chain management within the domain of environmental responsibility and concerns. The background of this research involves the issue of green supply chain management (GSCM) and the concept of the multiobjective integrated logistics model. More specifically, in this paper, we suggest the fuzzy multiobjective integrated logistics model with the transportation cost and demand fuzziness to solve green supply chain problems in the uncertain environment which is illustrated via the detailed numerical example. Results and the sensitivity analysis of the numerical example indicate that when the governmental subsidy value increased the profits of the reverse chain also increased. The finding shows that the governmental subsidy policy could remain of significant influence for used-product reverse logistics chain.