A multiobjective optimization model for optimal supplier selection in multiple sourcing environment
Keywords:
Multiobjective optimization, Fuzzy supplier selec- tion, Nonlinear optimization, Membership functions.Abstract
Supplier selection is an important concern of a firm’s competitiveness, more so in the context of the imperative of supply-chain management. In this paper, we use an approach to a multiobjective supplier selection problem in which the emphasis is on building supplier portfolios. The supplier evaluation and order allocation is based upon the criteria of expected unit price, expected score of quality and expected score of delivery. A fuzzy approach is proposed that relies on nonlinear S-shape membership functions to generate different efficient supplier portfolios. Numerical experiments conducted on a data set of a multinational company are provided to demonstrate the applicability and efficiency of the proposed approach to real-world applications of supplier selectionReferences
N. Aissaoui, M. Haouari and E. Hassini, Supplier selection and order lot sizing modeling: a review, Computers and Operations Research 34 (2007), 3516-3540.
A. Amid, S. H. Ghodsypour and C. O’Brien, Fuzzy multiobjective linear model for supplier selection in a supply chain, International Journal of Production Economics 104 (2006), 394-407.
A. Amid, S. H. Ghodsypour and C. O’Brien, A weighted additive fuzzy multiobjective model for the supplier selection problem under price breaks in a supply Chain, International Journal of Production Economics 121 (2009), 323-332.
A. Amid, S. H. Ghodsypour and C. O’Brien, A weighted maxmin model for fuzzy multi-objective supplier selection in a supply chain, Interna-tional Journal of Production Economics 131 (2011), 139-145.
F. Arikan, A fuzzy solution approach for multi objective supplier selec-tion, Expert Systems with Applications 40 (2013), 947-952.
M. Y. Bayrak, N. C¸elebi and H. Taskin, A fuzzy approach method for supplier selection, Production Planning and Control: The Management of Operations 18 (2007), 54-63.
R. Bellman and L. A. Zadeh, Decision making in a fuzzy environment, Management Science 17 (1970), 141-164.
J. Chai, J. N. K. Liu and E. W. T. Ngai, Application of decision-making techniques in supplier selection: a systematic review of literature, Expert Systems with Applications 40 (2013), 3872-3885.
C. T. Chen, C. T. Lin and S. F. Huang, A fuzzy approach for sup-plier evaluation and selection in supply chain management, International Journal of Production Economics 102 (2006), 289-301.
G. W. Dickson, An analysis of vendor selection systems and decisions, Journal of Purchasing 2 (1966), 5-17.
I. Erol, G. William and Jr. Ferrel, A methodology for selection problems with multiple, conflicting objectives and both qualitative and quantitative criteria, International Journal of Production Economics 86 (2003), 187-199.
B. Feng, Z. Fan and Y. Li, A decision method for supplier selection in multi-service outsourcing, International Journal of Production Eco-nomics 132 (2011), 240-250.
S. H. Ghodsypour and C. O’Brien, The total cost of logistics in supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraint, International Journal of Production Economics 73 (2001), 15-27.
P. Gupta, M. K. Mehlawat and A. Saxena, Asset portfolio optimization using fuzzy mathematical programming, Information Sciences 178 (2008), 1734-1755.
S.M. Guu, M. Mehlawat and S. Kumar, A multiobjective optimization framework for optimal selection of supplier portfolio, Optimization 63
(10) (2014), DOI:10.1080/02331934.2014.917306.
W. Ho, X. Xu and P. K. Dey, Multi-criteria decision making approaches for supplier evaluation and selection: a literature review, European Jour-nal of Operational Research 202 (2010), 16-24.
M. Inuiguchi, H. Ichihashi and Y. Kume, A solution algorithm for fuzzy linear programming with piecewise linear membership functions, Fuzzy Sets and Systems 34 (1990), 15-31.
C. Kahraman, U. Cebeci and Z. Ulukan, Multi-criteria supplier selection using fuzzy AHP, Logistics Information Management 16 (2003), 382-394.
B. Karpak, E. Kumcu and R. R. Kasuganti, An application of visual in-teractive goal programming: a case in vendor selection decisions, Journal of Multi-Criteria Decision Analysis 8 (1999), 93-105.
M. Kumar, P. Vart and P. Shankar, A fuzzy goal programming approach for supplier selection problem in a supply chain, Computer and Indus-trial Engineering 46 (2004), 69-85.
C. K. Kwang, W. H. Lp and J. W. K. Chan, Combining scoring method and fuzzy expert systems approach to supplier assessment: a case study, Integrated Manufacturing Systems 13 (2002), 512-519.
H. Leberling, On finding compromise solutions in multicriteria problems using the fuzzy min-operator, Fuzzy Sets and Systems 6 (1981), 105-118.
R. J. Li, and E. S. Lee, An exponential membership function for fuzzy multiple objective linear programming, Computers and Mathematics with Applications 22 (1991), 55-60.
C. C. Li, Y. P. Fun and J. S. Hung, A new measure for supplier perfor-mance evaluation, IIE Transactions 29 (1997), 753-758.
X. -Q. Li, B. Zhang and H. Li, Computing efficient solutions to fuzzy multiple objective linear programming problems, Fuzzy Sets and Systems 157 (2006), 1328-1332.
P. Parthiban, H. A. Zubar and P. Katakar, Vendor selection problem: a multi-criteria approach based on strategic decisions, International Jour-nal of Production Research 51 (2013), 1535-1548.
M. Punniyamoorthy, P. Mathiyalagan and P. Parthiban, A strategic model using structural equation modeling and fuzzy logic in supplier se-lection, Expert Systems with Applications 38 (2011), 458-474.
L. Scharge, Optimization Modeling with LINDO, Duxbury Press, CA, 1997.
L. Scharge, Optimization Modeling with LINGO, 6th edn., LINDO Sys-tems Inc., Chicago, Illinois, 2006.
K. Shaw, R. Shankar, S. S. Yadav and L. S. Thakur, Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for de-veloping low carbon supply chain, Expert Systems with Applications 39 (2012), 8182-8192.
R. N. Tiwari, S. Dharmar and J. R. Rao, Fuzzy goal programming-an additive model, Fuzzy Sets and Systems 24 (1987), 27-34.
M. Toloo and S. Nalchigar, A new DEA method for supplier selection in presence of both cardinal and ordinal data, Expert Systems with Appli-cations 38 (2011), 14726-14731.
W. Tsai and S. Hung, A fuzzy goal programming approach for green supply chain optimisation under activity-based costing and performance evaluation with a value-chain structure, International Journal of Pro-duction Research 47 (2009), 4991-5017.
J. Watada, Fuzzy portfolio selection and its applications to decision mak-ing, Tatra Mountains Mathematical Publications 13 (1997), 219-248.
C. A. Weber, J. R. Current and W. C. Benton, Vendor selection criteria and methods, European Journal of Operational Research 50 (1991), 2-18.
C. A. Weber and J. R. Current, A multiobjective approach to vendor selection, European Journal of Operational Research 68 (1993), 173-184.
A., Y¨ucel and A. F. G¨uneri, A weighted additive fuzzy programming approach for multi-criteria supplier selection, Expert Systems with Ap-plications 38 (2011), 6281-6286.
L. A. Zadeh, Fuzzy sets, Information and Control 8 (1965), 338-353.
H. -J. Zimmermann, Description and optimization of fuzzy systems, In-ternational Journal of General Systems 2 (1976), 209-215.
H. -J. Zimmermann, Fuzzy programming and linear programming with several objective functions, Fuzzy Sets and Systems 1 (1978), 45-55.
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