Volume 3 Issue 3 pp. 393-402 Spring, 2012


Supplier evaluation in manufacturing environment using compromise ranking method with grey interval numbers


Prasenjit Chatterjee, and Rupsa Chatterjee


Evaluation of proper supplier for manufacturing organizations is one of the most challenging problems in real time manufacturing environment due to a wide variety of customer demands. It has become more and more complicated to meet the challenges of international competitiveness and as the decision makers need to assess a wide range of alternative suppliers based on a set of conflicting criteria. Thus, the main objective of supplier selection is to select highly potential supplier through which all the set goals regarding the purchasing and manufacturing activity can be achieved. Because of these reasons, supplier selection has got considerable attention by the academicians and researchers. This paper presents a combined multi-criteria decision making methodology for supplier evaluation for given industrial applications. The proposed methodology is based on a compromise ranking method combined with Grey Interval Numbers considering different cardinal and ordinal criteria and their relative importance. A ‘supplier selection index’ is also proposed to help evaluation and ranking the alternative suppliers. Two examples are illustrated to demonstrate the potentiality and applicability of the proposed method.


DOI: 10.5267/j.ijiec.2011.12.007

Keywords: Supplier selection, Multi-criteria decision making Compromise ranking method, Grey interval number, Grey Supplier selection index

References

References Almeida, A.T. (2007). Multi criteria decision model for outsourcing contracts selection based on utility function and ELECTRE method. Computers & Operations Research, 34, 3569-3574.

Bayazit, O. (2006). Use of analytic network process in vendor selection decisions. Benchmarking: An International Journal, 13 (5), 566–579.

Chatterjee, P., Athawale V. M., & Chakraborty, S.(2009). Selection of materials using compromise ranking and outranking methods. Materials and Design, 30, 4043–4053.

Chou, S.Y., & Chang, Y.H. (2008). A decision support system for supplier selection based on a strategy-aligned fuzzy SMART approach. Expert Systems with Applications, 34, 2241-2253.

Chou, S.Y., Shen, C.Y., & Chang,Y.H. (2007). Vendor selection in a modified re-buy situation using a strategy-aligned fuzzy approach. International Journal Production Research, 5, 3113-3133.

Deng, J. L. ( 1982,).Control problem of grey system. System and Control Letters, 5, 288–294.

Deng, J. L. (1988). Introduction to Grey System Theory. The Journal of Grey Theory, 1, 1–24.

Feng B, Fan Z-P. & YanzhiLi, A. (2011). Decision method for supplier selection in multi-service outsourcing, International Journal of Production Economics. 132, 240–250.

Ghodsypour, S.H. & Brien, O.(1998). A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming. International Journal Production Economics, 56-57, 199-212.

Kasilingam, R.G., & Lee, C.P.(1996). Selection of vendors-A mixed-integer programming approach. Computers & Industrial Engineering, 31, 347-350.

Kumar, M., Vrat, P., & Shankar, R.(2000). A fuzzy programming approach for vendor selection problem in a supply chain. International Journal of Production Economics, 101, 273-285.

Liao C-N., & Kao H-P.(2011). An integrated fuzzy TOPSIS and MCGP approach to supplier selection in supply chain management. Expert Systems with Applications, 38, 10803–10811.

Lin, Y-H., Lee, P-C., & Ting, H-I.(2008). Dynamic multi-attribute decision making model with grey number evaluations. Expert Systems with Applications, 35, 1638–1644.

Liu, F.H.F., & Hai, H.L.(2005). The voting analytic hierarchy process method for selecting supplier. International Journal Production Economics, 97, 308-317.

Liu, F., Ding, F.Y., & Lall, V. (2000).Using Data Envelopment Analysis to compare vendors for vendor selection and performance improvement. Supply Chain Management, An International Journal, 5, 143-150.

Opricovic, S., & Tzeng, G.H.(2007). Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research, 178, 514-529.

Opricovic, S., & Tzeng, G.H.(2004). Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156, 445-455.

Opricovic, S., & Tzeng, G.H.(2003). Fuzzy multi criteria model for post-earthquake land-use planning. Natural Hazards Review, 4, 59-64.

Opricovic, S., & Tzeng, G.H.(2002). Multi criteria planning of post-earthquake sustainable reconstruction. Computer Aided Civil Infrastructure Engineering, 17, 211-220.

Pi, W.N., & Low, C.(2007). Supplier evaluation and selection via Taguchi loss functions and an AHP. International Journal of Advanced Manufacturing Technology, 27, 625-630.

Perçin, S. (2006). An application of the integrated AHP–PGP model in supplier selection. Measuring Business Excellence 10 (4), 34–49.

Rao, R.V. (2008). A decision making methodology for material selection using an improved compromise ranking method. Materials and Design, 29, 1949-1954.

Rao, R.V. (2007). Decision making in the manufacturing environment using graph theory and fuzzy multiple attribute decision making methods. London: Springer-Verlag.

Sanayei A., Farid M. S., & Yazdankhah A.(2010). Group decision making process for supplier selection with VIKOR under fuzzy environment. Expert Systems with Applications 37, 24–30.

Talluri, S., & Narasimhan, R.(2003). Vendor evaluation with performance variability: A max-min approach. European Journal of Operational Research, 146, 543-552.

Weber, C.A., Current, J.R.,& Desai, A.(1998). Non-cooperative negotiation strategies for vendor selection. European Journal of Operational Research, 108, 208-223.

Wu, D., & Olson, D.L (2008). A comparison of stochastic dominance and stochastic DEA for vendor evaluation. International Journal of Production Research, 46, 2313-2327.

Zeleny, M. (2002). Multiple criteria decision making. New York: McGraw Hill Publishers.