Abstract
The current paper presents a comprehensive methodology for supplier selection. In the first stage, the linguistic values expressed as trapezoidal fuzzy numbers are used to assess the weights of the criteria. The Axiomatic Fuzzy Set clustering (AFS) method, which handles ambiguity and fuzziness in the supplier selection problem effectively, is applied to cluster the suppliers and evaluate each potential supplier that aims at obtaining initial supplier ranking. In the second stage, the Fuzzy Analytic Hierarchy Process (FAHP) model is constructed to determine the weight of various quantitative and qualitative criteria. To address multiple decision criteria in supplier ranking, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is employed to select the final suppliers. A numerical example composed of 30 suppliers and 6 criteria is studied, and the experimental results show that the proposed evaluation framework is suitable for supplier selection decisions even with the dependent criteria/attributes.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
Aksoy A., Öztürk N. (2011) Supplier selection and performance evaluation in just-in-time production environments. Expert Systems with Applications 38(5): 6351–6359
Amid A., Ghodsypour S. H., O’Brien C. (2011) A weighted max–min model for fuzzy multi-objective supplier selection in a supply chain. International Journal of Production Economics 131(1): 139–145
Bevilacqua M., Ciarapica F. E., Giacchetta G. (2006) A fuzzy-QFD approach to supplier selection. Journal of Purchasing and Supply Management 12(1): 14–27
Chan F. T. S. (2003) Interactive selection model for supplier selection process: An analytical hierarchy process approach. International Journal Production Research 41(15): 3549–3579
Chan F. T. S., Kumar N. (2007) Global supplier development considering risk factors using fuzzy extended AHP-based approach. OMEGA-International Journal of Management Science 35(4): 417–431
Chang D. Y. (1996) Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research 95(3): 649–655
Chen Y.-J. (2011) Structured methodology for supplier selection and evaluation in a supply chain. Information Sciences 181(9): 1651–1670
Chena 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 102(2): 289–301
Finan J. S., Hurley W. J. (1999) Transitive calibration of the AHP verbal scale. European Journal of Operational Research 112(2): 367–372
Florez-Lopez R. (2007) Strategic supplier selection in the added-value perspective: A CI approach. Information Sciences 177(5): 1169–1179
Gumus A. T. (2009) Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology. Expert Systems with Application 36(2): 4067–4074
Ho W., Xu X., Dey P. K. (2010) Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research 202(1): 16–24
Hwang C. L., Yoon K. (1981) Multiple attribute decision making-methods and applications. Springer, Heidelberg
Jahanshahloo G. R., Lotfi F. H, Izadikhah M. (2006) Extension of the TOPSIS method for decision-making problems with fuzzy dta. Applied Mathematics and Computation 181(2): 1544–1551
Lee A. H. I. (2009a) 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. I. (2009b) A fuzzy AHP evaluation model for buyer-supplier relationships with the consideration of benefits, opportunities, costs and risks. International Journal of Production Research 47(15): 4255–4280
Li P., Fang S.-C. (2009) A survey on fuzzy relational equations, part I: Classification and solvability. Fuzzy Optimization and Decision Making 8(2): 179–229
Liang G.-S., Chou T.-Y., Han T.-C. (2005) Cluster analysis based on fuzzy equivalence relation. European Journal of Operational Researc 166(1): 160–171
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(9): 10803–10811
Liu X. D. (1998a) The fuzzy sets and systems based on AFS structure, EI Algebra and EII algebra. Fuzzy Sets and Systems 95(2): 179–188
Liu X. D. (1998b) The Fuzzy theory based on AFS algebras and AFS structure. Journal of Mathematical Analysis and Applications 217(2): 459–478
Liu, X. D., Chai, T. Y., & Wang, W. (2007). Approaches to the representations and logic operations for fuzzy concepts in the framework of Axiomatic Fuzzy Set Theory I, II. Information Sciences, 177 (4), 1007–1026, 1027–1045.
Liu X. D., Pedrycz W. (2009) Axiomatic fuzzy set theroy and its applications. Springer, Heidelberg
Liu X. D., Pedrycz W., Zhang Q. L. (2003) Axiomatics fuzzy sets logic. The Proceedings of IEEE International Conference on Fuzzy Systems 1: 55–60
Liu X. D., Wang W., Chai T. Y. (2005) The Fuzzy clustering analysis based on AFS theory. IEEE Transactions on Systems, Man and Cybernetics Part B 35(5): 1013–1027
Mafakheri F., Breton M., Ghoniem A. (2011) Supplier selection-order allocation: A two-stage multiple criteria dynamic programming approach. International Journal of Production Economics 132(1): 52–57
Saaty T. L. (1980) The analytic hierarchy process. McGraw-Hill, New York
Saen R. F. (2007) Suppliers selection in the presence of both cardinal and ordinal data. European Journal of Operational Research 183(2): 741–747
Shih H. S, Shyur H., Stanley L. J. (2007) An extension of TOPSIS for group decision making. Mathematical and Computer Modeling 45(7–8): 801–813
Talluri S., Narasimhan R., Nair A. (2006) Vendor performance with supply risk: A chance-constrained DEA approach. International Journal of Production Economics 100(2): 212–222
Wu D. D. (2010) A systematic stochastic efficiency analysis model and application to international supplier performance evaluation. Expert Systems with Applications 37(9): 6257–6264
Wu D. D., Zhang Y., Wu D., Olson D. L. (2010) Fuzzy multi-objective programming for supplier selection and risk modeling: A possibility approach. European Journal of Operational Research 100(3): 774–787
Xu X., Liu X., Chen Y. (2009) Applications of axiomatic fuzzy set clustering method on management strategic analysis. European Journal of Operational Research 198(1): 297–304
Yang T., Hung C. C. (2007) Multiple-attribute decision making methods for plant layout design problem. Robitics and Computer-Integrated Manufacturing 23(1): 126–137
Yeh W.-C., Chuang M.-C. (2011) Using multi-objective genetic algorithm for partner selection in green supply chain problems. Expert Systems with Applications 38(4): 4244–4253
Zadeh L.A. (1965) Fuzzy sets. Information and Control 8: 338–353
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Li, Y., Liu, X. & Chen, Y. Supplier selection using axiomatic fuzzy set and TOPSIS methodology in supply chain management. Fuzzy Optim Decis Making 11, 147–176 (2012). https://doi.org/10.1007/s10700-012-9117-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10700-012-9117-x