A two-phase fuzzy AHP - fuzzy TOPSIS model for supplier evaluation in manufacturing environment
Supplier selection is one of the most important issues in supply chain management (SCM) which greatly affects its performance and market competitiveness. In the recent years, supplier selection in SCM has become imperative to balance between the ordinal and cardinal criteria. This paper proposes a two-phase model which aims to evaluate and select suppliers using an integrated Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Technique for Ordering Preference by Similarity to Ideal Solution (FTOPSIS) methods. A fully developed model consisting of several evaluation criteria, both quantitative and qualitative in nature, as assessed by FAHP method to estimate the criteria weights, while FTOPSIS method is used to rank the potential suppliers that have been singled out through expert assessment. The proposed model is a support tool in the optimization of the purchasing process, and it provides the possibility of realizing additional savings by developing stronger cooperation with the optimal supplier.
Bhutta, K. S.; Huq, F. 2002. Supplier selection problem: a comparison of the total cost of ownership and analytic hierarchy process approaches, Supply Chain Management: An International Journal, 7(3): 126-135.
Çebi, F.; Bayraktar, D. 2003. An integrated approach for supplier selection, Logistics information management, 16(6): 395-400.
Chang, D. Y. 1996. Applications of the extent analysis method on fuzzy AHP, European journal of operational research, 95(3): 649-655.
Chen, C. T. 2000. Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy sets and systems, 114(1): 1-9.
Chen, S. J.; Hwang, C. L. 1992. Fuzzy multiple attribute decision making: Methods and applications. Berlin: Springer
Chen, Z., & Yang, W. (2011). An MAGDM based on constrained FAHP and FTOPSIS and its application to supplier selection. Mathematical and Computer Modelling, 54(11), 2802-2815.
De Boer, L.; Labro, E.; Morlacchi, P. 2001. A review of methods supporting supplier selection, European journal of purchasing & supply management, 7(2): 75-89.
Dickson, G. W. 1966. An analysis of vendor selection and the buying process, Journal of Purchasing, 2(1): 5-17.
Dincer, H., Hacioglu, U., Tatoglu, E., & Delen, D. (2016). A fuzzy-hybrid analytic model to assess investors' perceptions for industry selection. Decision Support Systems, 86, 24-34.
Ellram, L. M. 1990. The supplier selection decision in strategic partnerships, Journal of Purchasing and materials Management, 26(4): 8-14.
Eraslan, E., & Atalay, K. D. (2014). A Comparative Holistic Fuzzy Approach for Evaluation of the Chain Performance of Suppliers. Journal of Applied Mathematics, 2014.
Ertuğrul, İ.; Karakaşoğlu, N. 2008. Comparison of fuzzy AHP and fuzzy TOPSIS methods for facility location selection, The International Journal of Advanced Manufacturing Technology, 39(7-8): 783-795.
Ghodsypour, S. H.; O’brien, C. 2001. The total cost of logistics in supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraint, International journal of production economics, 73(1): 15-27.
Ghodsypour, S. H.; O'Brien, C. 1998. A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming, International journal of production economics, 56: 199-212.
Ginevičius, R; Podvezko, V., 2008. Multicriteria evaluation of Lithuanian banks from the perspective of their reliability for clients, Journal of Business Economics and Management, (4): 257-267.
Gunasekaran, A.; Ngai, E. W. 2004. Information systems in supply chain integration and management, European Journal of Operational Research, 159(2): 269-295.
Hwang, C. L.; Yoon, K. 1981. Multiple attributes decision making methods and applications. Berlin: Springer.
Kagnicioglu C. H. 2006 A Fuzzy Multiobjective Programming Approach for Supplier Selection in a Supply Chain, The Business Review, Cambridge. Hollywood, 6(1): 107-115.
Karpak, B.; Kumcu, E.; Kasuganti, R. R. 2001. Purchasing materials in the supply chain: managing a multi-objective task, European Journal of Purchasing & Supply Management, 7(3): 209-216.
Knezevic, B.; Delic, M.; Lovric, S. 2012. Evaluation Of Suppliers As A Basis Of Strategic Procurement, Business Logistics in Modern Management, 12: 61-74.
Kwong, C. K.; Bai, H. 2003. Determining the importance weights for the customer requirements in QFD using a fuzzy AHP with an extent analysis approach, Iie Transactions, 35(7): 619-626.
Lasch, R.; Janker, C. G. 2005. Supplier selection and controlling using multivariate analysis, International Journal of Physical Distribution & Logistics Management, 35(6): 409-425.
Lee, A. H. 2009. A fuzzy supplier selection model with the consideration of benefits, opportunities, costs and risks, Expert systems with applications, 36(2): 2879-2893.
Lee, A. H.; Chen, W. C.; Chang, C. J. 2008. A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan, Expert systems with applications, 34(1): 96-107.
Mohaghar, A., Fathi, M. R., & Jafarzadeh, A. H. (2013). A Supplier Selection Method Using AR-DEA and Fuzzy VIKOR. International Journal of Industrial Engineering: Theory, Applications and Practice, 20(5-6).
Önüt, S.; Kara, S. S.; Işik, E. 2009. Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company. Expert Systems with Applications, 36(2): 3887-3895.
Prakash, C., & Barua, M. K. (2016). An analysis of integrated robust hybrid model for third-party reverse logistics partner selection under fuzzy environment.Resources, Conservation and Recycling, 108, 63-81.
Saaty, T. L. 1980. The Analytic Hierarchy Process, Mc Graw‐Hill, NewYork
Puška, L. A., Kozarević, S., Stević, Ž., & Stovrag, J. (2018). A new way of applying interval fuzzy logic in group decision making for supplier selection. Economic Computation & Economic Cybernetics Studies & Research, 52(2).
Shukla, R. K.; Garg, D.; Agarwal, A. 2014. An integrated approach of Fuzzy AHP and Fuzzy TOPSIS in modeling supply chain coordination, Production & Manufacturing Research, 2(1): 415-437.
Tüysüz, F.; Kahraman, C. 2006. Project risk evaluation using a fuzzy analytic hierarchy process: an application to information technology projects, International Journal of Intelligent Systems, 21(6): 559-584.
Verma, R.; Pullman, M. E. 1998. An analysis of the supplier selection process, Omega, 26(6): 739-750.
Weber, C. A.; Current, J. R.; Benton, W. C. 1991. Vendor selection criteria and methods, European journal of operational research, 50(1): 2-18.
Yazdani, M.; Hashemkhani Z. S, Zavadskas, E.K. 2016. New integration of MCDM methods and QFD in the selection of green suppliers, Journal of Business Economics and Management,1-17.
Yazdani-Chamzini, A. (2014). An integrated fuzzy multi criteria group decision making model for handling equipment selection. Journal of Civil Engineering and Management, 20(5), 660-673.
Yazdani-Chamzini, A., Haji Yakchali, S., & Kazimieras Zavadskas, E. (2012). Using a integrated MCDM model for mining method selection in presence of uncertainty. Ekonomska istraživanja, 25(4), 869-904.
Yu, X.; Guo, S.; Guo, J.; Huang, X. 2011. Rank B2C e-commerce websites in e-alliance based on AHP and fuzzy TOPSIS, Expert Systems with Applications, 38(4): 3550-3557.
Zadeh, L. A. 1965. Fuzzy sets, Information and control, 8(3): 338-353.
Zeydan, M.; Çolpan, C.; Çobanoğlu, C. 2011. A combined methodology for supplier selection and performance evaluation, Expert Systems with Applications, 38(3): 2741-2751.