A Comprehensive Fuzzy Multiobjective Supplier Selection Model under Price Brakes and Using Interval Comparison Matrices

Document Type : Research Paper

Authors

1 Technical and Engineering Department, Alzahra University, Tehran, Iran

2 Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran

Abstract

The research on supplier selection is abundant and the works usually only consider the critical success factors in the buyer–supplier relationship. However, the negative aspects of the buyer–supplier relationship must also be considered simultaneously. In this paper we propose a comprehensive model for ranking an arbitrary number of suppliers, selecting a number of them and allocating a quota of an order to them considering three objective functions: minimizing the net cost, minimizing the net rejected items and minimizing the net late deliveries. The two-stage logarithmic goal programming method for generating weights from interval comparison matrices (Wang et al. 2005) is used for ranking and selecting the suppliers. It is assumed that the suppliers give price discounts. A fuzzy multiobjective model is formulated in such a way as to consider imprecision of information. A numerical example is given to explain how the model is applied.

Keywords

Main Subjects


[1] Amid A.,Ghodsypour S.H., O’Brien C.A. (2006), Fuzzy multiobjective linear model for supplier selection in a supply chain; International Journal of Production Economics 104; 394–407.
[2] Amid A., Ghodsypour S.H., O’Brien C.A. (2008), weighted additive fuzzy multiobjective model for the supplier selection problem under price breaks in a supply chain; International Journal of Production Economics 121; 323-332.
[3] Amy H.I. Lee (2008), A fuzzy supplier selection model with the consideration of benefits, opportunities, costs and risks; Expert Systems with Applications 36; 2879-2893.
[4] Arbel A. (1989), Approximate articulation of preference and priority derivation; European Journal of Operational Research; 43317–326.
[5] Arbel A. (1991), A linear programming approach for processing approximate articulation of preference, in: P. Korhonen, A. Lewandowski, J. Wallenius, (Eds.), Multiple Criteria Decision Support; Lecture Notes in Economics and Mathematical Systems 356, Springer, Berlin; 79–86.
[6] Arbel A., Vargas L.G. (1990), The analytic hierarchy process with interval judgments, in: A. Goicoechea, L. Duckstein, S. Zoints, (Eds.), 9th Internat. Conference on Multiple criteria decision making, Fairfax, Virginia, Springer, New York; 61–70.
[7] Arbel A., Vargas L.G. (1993), Preference simulation and preference programming: robustness issues in priority deviation; European Journal of Operational Research 69; 200–209.
[8] Bonder C.G. E., deGraan J.G., Lootsma. F.A. (1989), Multicriteria decision analysis with fuzzy pairwise comparisons; Fuzzy Sets and Systems 29; 133–143.
[9] Buckley J.J. (1985), Fuzzy hierarchical analysis; Fuzzy Sets and Systems 17; 233–247.
[10] Buckley J.J., Feuring T., Hayashi Y. (2001), Fuzzy hierarchical analysis revisited; European Journal of Operational Research 129; 48–64.
[11] Conde E., de la Paz Rivera Pérez M.(2010), A linear optimization problem to derive relative weights using an interval judgement matrix; European Journal of Operational Research 201(2); 537-544.
[12] Csutora R., Buckley J.J. (2001), Fuzzy hierarchical analysis: the Lamda–Max method; Fuzzy Sets and Systems 120; 181–195.
[13] Dempsey W.A. (1978), Vendor selection and buying process; Industrial Marketing Management 7; 257-267.
[14] Dickson G.W. (1966), An analysis of vendor selection systems and decisions; Journal of Purchasing 2(1); 5-17.
[15] Dopazo E., Ruiz-Tagle M.A. (2009), GP formulation for aggregating preferences with interval assessments; Lecture Notes in Economics and Mathematical Systems 618; 47-54.
[16] Dopazo E., Ruiz-Tagle M., Robles J. (2007), Preference learning from interval pairwise data. A distance-based approach; Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4881 LNCS; 240-247.
[17] Geringer J.M. (1988), Joint venture partner selection: Strategies for develop countries; Westport, Quorum Books.
[18] 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.
[19] Haines L.M. (1998), A statistical approach to the analytic hierarchy process with interval judgments.(I).Distributions on feasible regions; European Journal of Operational Research 110; 112–125.
[20] Hong G.H., Park S.C., Jang D.S., Rho H.M. (2005), An effective supplier selection method for constructing a competitive supply relationship; Expert Systems with Applications 28; 629–639.
[21] Islam R., Biswal M.P., Alam S.S. (1997), Preference programming and inconsistent interval judgments; European Journal of Operational Research 97; 53–62.
[22] Kaslingam R., Lee C. (1996), Selection of vendors – a mixed integer programming approach; Computers and Industrial Engineering 31; 347–350.
[23] Kress M. (1991), Approximate articulation of preference and priority derivation—A comment; European Journal of Operational Research 52; 382–383.
[24] Kumar M., Vrat P., Shankar R. (2004), A fuzzy goal programming approach for vendor selection problem in a supply chain; Computers and Industrial Engineering 46; 69–85.
[25] Kumar M., Vrat P., Shankar R. (2006), A fuzzy programming approach for vendor selection problem in a supply chain; International Journal of Production Economics 101; 273–285.
[26] Lee A.H.I. (2009), A fuzzy AHP evaluation model for buyer–supplier relationships with the consideration of benefits, opportunities, costs and risks; International Journal of Production Research 47; 4255-4280
[27] Leung L.C., Cao D. (2000), On consistency and ranking of alternatives in fuzzy AHP; European Journal of Operational Research 124; 102–113.
[28] Lewis J.D. (1990), Partnership for profit: structuring and managing strategic alliance; The Free Press, New York.
[29] Lin C.-W.R., Chen H.-Y. S. (2004), A fuzzy strategic alliance selection framework for supply chain partnering under limited evaluation resources; Computers in Industry 55; 159–179.
[30] Liu F.-H.F, Hai H.L. (2005), The voting analytic hierarchy process method for selecting supplier; International Journal of Production Economics 97; 308–317.
[31] Lorange P., Roos J., Bronn P.S. (1992), Building successful strategic alliances; Long Range Planning 25(6); 10–17.
[32] Mikhailov L. (2002), Fuzzy analytical approach to partnership selection in formation of virtual enterprises; Omega: International Journal of Management Science 30; 393–401.
[33] Mikhailov L. (2003), Deriving priorities from fuzzy pairwise comparison judgments; Fuzzy Sets and Systems 134; 365–385.
[34] Mikhailov L. (2004), Group prioritization in the AHP by fuzzy preference programming method; Comput. Oper. Res 31; 293–301.
[35] Moreno-Jiménez. J.M. (1993), A probabilistic study of preference structures in the analytic hierarchy process within terval judgments; Math. Comput. Modeling 17 (4/5); 73–81.
[36] Muralidharan C., Anantharaman N., Deshmukh S.G. (2002), A multi-criteria group decisionmaking model for supplier rating; Journal of Supply Chain Management 38(4); 22–33.
[37] Narasimahn R. (1983), An analytical approach to supplier selection; Journal of Purchasing and Materials Management 19(4); 27–32.
[38] Nydick R.L., Hill R.P. (1992), Using the analytic hierarchy process to structure the supplier selection procedure; Journal of Purchasing and Materials Management 25(2); 31–36.
[39] Partovi F.Y., Burton J., Banerjee A. (1989), Application of analytic hierarchy process in operations management; International Journal of Operations and Production Management 10(3); 5–19.
[40] Ravindran A.R., Bilsel R.U., Wadhwa V., Yang T. (2010), Risk adjusted multicriteria supplier selection models with applications; International Journal of Production Research 48(2); 405-424.
[41] Saaty R.W. (2003), Decision making in complex environment: The analytic hierarchy process (AHP) for decision making and the analytic network process (ANP) for decision making with dependence and feedback; Pittsburgh, Super Decisions.
[42] Saaty T.L., Vargas L.G. (1987), Uncertainty and rank order in the analytic hierarchy process; European Journal of Operational Research 32 ; 107–117.
[43] Saaty T.L. (2004), Fundamentals of the analytic network processmultiple networks with benefits, opportunities, costs and risks; Journal of Systems Science and Systems Engineering 13(3); 348–379.
[44] Salo A., Hämäläinen R.P. (1992), Processing interval judgments in the analytic hierarchy process, in: A. Goicoechea, L. Duckstein, S. Zoints, (Eds.); Proc. 9th Internat. Conference on Multiple Criteria Decision Making; Fairfax, Virginia, Springer, NewYork; 359–372.
[45] Salo A., Hämäläinen R.P. (1995), Preference programming through approximate ratio comparisons, European Journal of Operational Research 82; 458–475.
[46] Van Laarhoven P.J.M., Pedrycz W. (1983), A fuzzy extension of Saaty’s priority theory; Fuzzy Sets and Systems 11; 229–241.
[47] Wang Y.M., Chin K.S. (2006), An eigenvector method for generating normalized interval and fuzzy weights; Applied Mathematics and Computation 181(2); 1257-1275.
[48] Wang Y.M., Yang J.B.,Xu D.L. (2005), A two-stage logarithmic goal programming method for generating wehghts from interval comparison matrices; Fuzzy Sets and Systems 152; 475–498.
[49] Weber C.A., Current J.R. (1993), A multi-objective approach to vendor selection; European Journal of Operational Research 68(2); 173–184.
[50] Weber C.A., Current J.R., Benton W.C. (1991), Vendor selection criteria and methods; European Journal of Operational Research 50; 1-17.
[51] Weber C.A., Current J.R., Desai A. (1998), Non-cooperative negotiation strategies for vendor selection; European Journal of Operational Research 108; 208–223.
[52] Weber C.A, Desai A. (1996), Determination of path to vendor market efficiency using parallel coordinates representation: A negotiation tool for buyers; European Journal of Operational Research 90; 142–155.
[53] 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 200(3); 774-787.
[54] Xu R. (2000), Fuzzy least-squares priority method in the analytic hierarchy process; Fuzzy Sets and Systems 112; 359–404.
[55] Xu R., Zhai X. (1996), Fuzzy logarithmic least squares ranking method in analytic hierarchy process; Fuzzy Sets and Systems 77; 175–190.
[56] Zimmermann H.J. (1978), Fuzzy programming and linear programming with several objectives functions; Fuzzy Sets and Systems 1; 45-55.