Fuzzy Multicriteria Model for Ranking Suppliers in Manufacturing Company
Ključne riječi:
Multi-criteria decision making, supplier evaluation, Fuzzy AHP, COPRAS, procurement, research, decision support systemsSažetak
By using the methods of multi-criteria analysis it is possible to make decisions which have significant influence on companies' business. The aim of this paper is to evaluate different suppliers using the integrated model that recognizes a combination of fuzzy AHP (Analytical Hierarchy Process) and the COPRAS method. Based on six criteria, the expert team was formed to compare them, so determination of their significance is being done with fuzzy AHP method. Expert team also compares suppliers according to each criterion and on the base of triangular fuzzy numbers. Based on their inputs, COPRAS method is used to estimate potential solutions. Suggested model accomplishes certain advantages in comparison with previously used traditional models which were used to make decisions about evaluation and choice of supplier. It is vital to make the right decision when selecting a supplier, because the optimal choice ensures lower cost and higher quality of the product itself, and therefore more competitiveness in the market.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Reference
Ayhan, M. B. (2013), “A Fuzzy AHP approach for supplier selection problem: a case study in a gear motor company”. International Journal of Managing Value and Supply Chains Vol. 4 No.3, pp. 11-23.
Benyoucef, M., Canbolat, M. (2007), “Fuzzy AHP-based supplier selection in e-procurement”. International Journal of Services and Operations Management, Vol. 3 No.1, pp. 172-192.
Chan, F. T., Kumar, N. (2007), “Global supplier development considering risk factors using fuzzy extended AHP-based approach”. Omega, Vol. 35 No.4, pp. 417-431.
Chang, D. Y. (1996), “Applications of the extent analysis method on fuzzy AHP”. European journal of operational research, Vol.95 No.3, pp. 649-655.
Chen, C. T., Lin, C. T., Huang, S. F. (2006), “A fuzzy approach for supplier evaluation and selection in supply chain management”. International journal of production economics, Vol. 102 No.2, pp. 289-301.
Ertugrul, I., Karakasoglu, N. (2006), “The fuzzy analytic hierarchy process for supplier selection and an application in a textile company”. Proceedings of 5th international symposium on intelligent manufacturing systems, pp. 195-207.
Ginevičius, R. (2008), “Normalization of quantities of various dimensions”. Journal of business economics and management, Vol. 9 No.1, pp. 79-86.
Kaklauskas, A., Zavadskas, E. K., Raslanas, S., Ginevicius, R., Komka, A., Malinauskas, P. (2006), “Selection of low-e windows in retrofit of public buildings by applying multiple criteria method COPRAS: A Lithuanian case”. Energy and Buildings, Vol. 38 No.5, pp. 454-462.
Kilincci, O., Onal, S. A. (2011), “Fuzzy AHP approach for supplier selection in a washing machine company”. Expert systems with Applications, Vol. 38 No.8, pp. 9656-9664.
Lee, A. H. (2009), “A fuzzy supplier selection model with the consideration of benefits, opportunities, costs and risks”. Expert systems with applications, Vol. 36 No.2, pp. 2879-2893.
Saaty, T. L. (1980), “The Analytic Hierarchy Process”, McGraw‐Hill, NewYork
Saaty, T. L. (2008), “Decision making with the analytic hierarchy process”. International journal of services sciences, Vol. 1 No.1, pp. 83-98.
Saaty, T. L., Vargas, L. G. (2012), “Models, methods, concepts & applications of the analytic hierarchy process”Springer Science & Business Media Vol. 175.
Zadeh, L.A. (1965), “Fuzzy sets”. Information and Control, Vol. 8 No.3, pp. 338-353.
Zavadskas, E. K., Kaklauskas, A., Kvederytė, N. (2001), “Multivariant design and multiple criteria analysis of a building life cycle”. Informatica, Vol.12 No.1, pp. 169-188.
Zavadskas, E. K., Kaklauskas, A., Sarka, V. (1994), “The new method of multicriteria complex proportional assessment of projects”. Technological and Economic Development of Economy, Vol. 1 No.3, pp. 131-139.
