Evaluating and Selecting Two-Layers of Suppliers in Green Supply Chain using Hierarchical Fuzzy Topsis based on Alpha Levels

Document Type : Original Article

Authors

1 Assistant Professor, University of Kurdistan.

2 MA. Student, University of Kurdistan.

Abstract

Developments in the world of business and new requirements leads to new attitudes which is considered essential for those involved in production and trade. New approaches and attitudes are developed about supply chain that leads to a green one.  The study examined two layer suppliers: first layer (providers of the parts and raw material directly to the manufacturer), and the second layer (providers of parts and raw material for the first layer) finally the study searched for the optimal supplier among them in each layer. To rank suppliers the below item were applieid: the concepts of first and second layers suppliers, green factor, using the proposed method entitled as s"second layer". Then their associated fuzzy numbers were calculated through Hierarchical Fuzzy TOPSIS method based on different levels of alpha. The study tries to establish a systematic approach for evaluating and selecting two layers of suppliers an dat he same time taking into account environmental factors. Manufacturer Stove Companies were the study sample.

Keywords

References

1. Aissaoui, N., Haouari, M. & Hassini, E. (2007). Supplier selection and order lot sizing modeling : A review. Comput. Oper. Res., 34(12), 3516–3540.
2. Bulsara, H. P., Qureshi, M. N., & Patel, H. (2016).  Green supply chain performance measurement: an exploratory study. Int. J. Logist. Syst. Manag., 23(4), 476– 498.
3. Dickson, G. W. (1996). An analysis of vendor selection systems and decisions. J. Purch., 2(1), 5–17.
4. Faghih. N., Raenai. H., Mohammadi., A., Samadi. A., Mousavi. M., Ghafornyan.M. (2013). Assessment of service supply chain of IRAN fixed communications by system dynamics approach. Journal of Industrial Management Perspective, 11, 111-138 (In Persion).
5. Ghazanfari, M., Fatallah, M. (2006).A comprehensive approach to managing supply chain, Tehran, Iran  university of Science and Technology.
6. Govindan, K., Rajendran, S., Sarkis, J., & Murugesan, P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection : a literature review. J. Clean. Prod., 98, 66–83.
7. Ha, S.H., & Krishnan, R. (2008). A hybrid approach to supplier selection for the maintenance of a competitive supply chain. Expert Syst. Appl., 34(2), 1303–1311.
8. Houshmandi. M., Amiri. M., Olfat. L. (2013). An integrated approach for supplier selection in a supply chain: IT capabilities approach. Journal of Industrial Management Perspective, 8, 91-115 (In Persion).
9. Hu, A. H. (2013). Using DEMATEL to develop a carbon management model of supplier selection in green supply chain management. J. Clean. Prod., 56, 164–172.
10. Jadidi, O.,  Hong, T. S., Firouzi, F., Yusuff, R. M., & Zulkifli, N. (2008). TOPSIS and fuzzy multi-objective model integration for supplier selection problem.  J. Achievements Mater. Manuf. Eng., 31(2), 762–769.
11. Jafarnezhad, A., Esmaeilian, M., Rabieh, M. (2009). Evaluation and selection of supplier in supply chain in case of single sourcing with FUZZY approach. Modarres Human Science, 12, 127-153.
12. Jain, v., Benyoucef, L., & Deshmukh, S.D. (2008). Strategic supplier selection: some emerging issues and challenges. Int. J. Logist. Syst. Manag., 5(1–2), 61–88.
13. Kannan, D., Beatriz Lopes de Sousa Jabbour, A., & José Chiappetta Jabbour, CH. (2014). Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company. European Journal of Operational Research, 233, 432-447.
14. Kuo, R. J., Wang, Y. C., & Tien, F. C. (2010). Integration of artificial neural network and MADA methods for green supplier selection. Journal of Cleaner Production, 18(12), 1161–1170.
15. Lambert, D.M., & and Cooper, M. C. (2000). Issues in supply chain management. Ind. Mark. Manag, 29(1), 65-83.
16. Liao, Z., &  Rittscher, J. (2007). A multi-objective supplier selection model under stochastic demand conditions. Int. J. Prod. Econ., 105(1), 150–159.
17. Liu, F. F., & Hai, H. L. (2005). The voting analytic hierarchy process method for selecting supplier. Interantional J. Prod. Econ., 97(3), 308–317.
18. Liu, J.,  Ding, F. & Vinod, L. (2000). Using data envelopment analysis to compare suppliers for supplier selection and performance improvement. Supply Chain Manag. An Int. J., 5(3), 143–150.
19. Min, H., & Galle, W. P. (2001). Green purchasing practices of US firms. International Journal of Operations & Production Management, 21(9), 1222–1238.
20. Morovati. A., Kazemi. F., Hayati. M. (2013).  Supplier selection with fuzzy MCDM approach and fuzzy QFD (Case Study: Snow-Pars co. of Yazd). Journal of Industrial Management Perspective, 10, 129-146 (In Persion).
21. Najafi Noubar, M., & Setak, M. (2010). A New Approach For Supplier Selection Process From The Features Of Second Layer Suppliers Point oF View. Interantional J. Ind. Eng. Prod. Res., 21(1), 35–44.
22. Osman, H., & Demirli, K. (2010). A bilinear goal programming model and a modified Benders decomposition algorithm for supply chain reconfiguration and supplier selection. Int. J. Prod. Econ., 124(1), 97–105.
23. Osman, H., & Demirli, K. (2012). Economic lot and delivery scheduling problem for multi-stage supply chains. Int. J. Prod. Econ.,136(2), 275–286.
24. Pak, S. (2013).  A review of the literature and a framework for green supply chain management. in The 2013 IBEA, International Conference on Business, Economics, and Accounting, , 20–23.
25. Pi, W.N., & Low, C. (2006). Supplier evaluation and selection via Taguchi loss functions and an AHP. Interantional J. Adv. Manuf. Technol., 27(5–6), 625–630.
26. Rabieh, M., Azar, A., Modarres, M., & Fetanat, M., (2011). Mathematical Modeling for Multi Objective Robust Sourcing Problem: An Approach in Reduction of Supply Chain Risk (Case study: IKCO Supply Chain). Journal of Indusrial Mangement Perspective, 1, 57-77 (In Persion).
27. Rabieh, M., Esmaelian, M., (2011).Designing a Fuzzy Non-Linear Model of Supplier Selection in Case of Multiple Sourcing. Journal of Indusrial Mangement Perspective, 4, 81-105 (In Persion).
28. Roshandel, J., Miri-Nargesi, S., & Hatami-Shirkouhi, L. (2013). Evaluating and selecting the supplier in detergent production industry using hierarchical fuzzy TOPSIS. Applied Mathematical Modelling, 37, 10170-10181.
29. Saen, R. F. (2007). Suppliers Selection in the Presence of both Cardinal and Ordinal Data. Eur. J. Oper. Res., 183(2), 741–47.
30. Setak, M., Sharifi, S. (2011).An integrated mathematical model for selecting the first and second layers of suppliers in a supply chain. International Journal of Industrial Engineering & Production Management., 22, 91-98.
31. Shaw, K.,  Shankar, K., Yadav, S., & Thakur, L. S. (2012). Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain. Expert Syst. Appl., 39(9), 8182–8192.
32. Shen, L., Olfat, L., Govindan, K., Khodaverdi, R., Diabat, A. (2013). A fuzzy multi criteria approach for evaluating green supplier’s performance in green supply chain with linguistic preferences. Resources, Conservation and Recycling., 74, 170–179.
33. Wang, Y., & Elhag, T. (2006). Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Expert Systems with Applications., 31, 309–319.
Journal of Industrial Management Perspective
Volume 6, Issue 2 - Serial Number 22
September 2016
Pages 91-121

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