Assessment of Green Supplier Development Programs by a New Group Decision-Making Model Considering Possibilistic Statistical Uncertainty

Document Type : Research Paper

Authors

1 School of Industrial Engineering, College of Engineering

2 School of Industrial Engineering, College of Engineering, University of Tehran

Abstract

The assessment and selection of green supplier development programs are an intriguing and functional research subject. This paper proposes a group decision-making approach considering possibilistic statistical concepts under uncertainty to assess green supplier development programs (GSDPs) via interval-valued fuzzy sets (IVFSs). Possibility theory is employed to regard uncertainty by IVFSs. A new version of a technique for order preference by similarity to ideal solution (TOPSIS) is proposed to solve the decision problem. Possibilistic mean, standard deviation, and cube-root of skewness matrices are provided to consider relative closeness coefficients. In addition, a new version of an entropy method is introduced to obtain criteria weights under uncertainty. Finally, an illustrative example in an automobile manufacturing system is given to show the capability of the presented approach in addition to comparisons with recent fuzzy decision techniques for GSDPs. 

Keywords

References

Akman, G. (2015). Evaluating suppliers to include green supplier development programs via fuzzy c-means and VIKOR methods. Computers & industrial engineering, 86, 69-82.
Awasthi, A., & Kannan, G. (2016). Green supplier development program selection using NGT and VIKOR under fuzzy environment. Computers & Industrial Engineering, 91, 100-108.
Bai, C., & Sarkis, J. (2010). Green supplier development: analytical evaluation using rough set theory. Journal of Cleaner Production, 18(12), 1200–1210.
Beamon, B. M. (1998). Supply chain design and analysis: models and methods. International journal of production economics, 55(3), 281-294.
Blome, C., Hollos, D., & Paulraj, A. (2014). Green procurement and green supplier development: antecedents and effects on supplier performance. International Journal of Production Research, 52(1), 32-49.
Chauhan, S. S., Nagi, R., & Proth, J. M. (2004). Strategic capacity planning in supply chain design for a new market opportunity. International journal of production research, 42(11), 2197-2206.
Deng, X., & Li, R. (2014). Gradually tolerant constraint method for fuzzy portfolio based on possibility theory. Information Sciences, 259, 16-24.
Dou, Y., Zhu, Q., & Sarkis, J. (2014). Evaluating green supplier development programs with a grey-analytical network process-based methodology. European Journal of Operational Research, 233(2), 420-431.
Fu, X., Zhu, Q., & Sarkis, J. (2012). Evaluating green supplier development programs at a telecommunications systems provider. International Journal of Production Economics, 140(1), 357-367.
Glock, C. H., Grosse, E. H., & Ries, J. M. (2017). Reprint of “Decision support models for supplier development: Systematic literature review and research agenda”. International Journal of Production Economics, 194, 246-260.
Lee, T. R., Phuong Nha Le, T., Genovese, A., & Koh, L. S. (2011). Using FAHP to determine the criteria for partner’s selection within a green supply chain: the case of hand tool industry in Taiwan. Journal of Manufacturing Technology Management, 23(1), 25-55.
Li, X., Qin, Z., & Kar, S. (2010). Mean-variance-skewness model for portfolio selection with fuzzy returns. European Journal of Operational Research, 202(1), 239-247.
Luthra, S., Govindan, K., Kannan, D., Mangla, S. K., & Garg, C. P. (2017). An integrated framework for sustainable supplier selection and evaluation in supply chains. Journal of Cleaner Production, 140, 1686-1698.
Min, H., & Galle, W. P. (2001). Green purchasing practices of US firms. International Journal of Operations & Production Management, 21(9), 1222-1238.
Nikbakhsh, E. (2009). Green supply chain management. In Supply chain and logistics in national, international and governmental environment (pp. 195-220). Physica-Verlag HD.
Qin, J., Liu, X., & Pedrycz, W. (2017). An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment. European Journal of Operational Research, 258(2), 626-638.
Santoso, T., Ahmed, S., Goetschalckx, M., & Shapiro, A. (2005). A stochastic programming approach for supply chain network design under uncertainty. European Journal of Operational Research, 167(1), 96-115.
Tian, G., Zhang, H., Feng, Y., Wang, D., Peng, Y., & Jia, H. (2018). Green decoration materials selection under interior environment characteristics: A grey-correlation based hybrid MCDM method. Renewable and Sustainable Energy Reviews, 81, 682-692.
Ye, F., & Lin, Q. (2013). Partner selection in a virtual enterprise: a group multiattribute decision model with weighted possibilistic mean values. Mathematical Problems in Engineering, 2013.
Zhang, W. G., Wang, Y. L., Chen, Z. P., & Nie, Z. K. (2007). Possibilistic mean–variance models and efficient frontiers for portfolio selection problem. Information Sciences, 177(13), 2787-2801.
Journal of Quality Engineering and Production Optimization
Volume 3, Issue 2
November 2018
Pages 1-10

Files

Share

How to cite

Statistics