Volume- 2
Issue- 5
Year- 2014
Article Tools: Print the Abstract | Indexing metadata | How to cite item | Email this article | Post a Comment
Dr Raosaheb V Latpate , .
Today’s market is highly competitive. The role of supply chain managers is to select best suppliers because major part of the capital is spent on purchasing raw material/semi finished items. The strategic decision of supply chain is to minimize the expenses on the purchase of items. There are several criteria involved in this problem; such as cost, quality, on-time delivery and long term relationship. Some of the criteria are quantitative in nature and some the criteria are qualitative in nature. Qualitative criteria are expressed in triangular fuzzy numbers. It requires defuzzification; the graded mean integration (GMI) representation method is used. Again all of these criteria are conflicting in nature that’s why fuzzy programming is used. For formulating the crisp model, it requires defuzzification; fuzzy compensatory operator is applied. This model gives us the idea about supplier selection as well as order quantity from each selected suppliers. Also, the numerical example is given to illustrate the above methods.
[1]. Amid, A., Ghodsypour, S.H., O’Brien, C., “Fuzzy Multiobjective linear model for supplier selection in a supply chain”. International Journal of Production Economics, 104, 394- 407,2005.
[2]. Amid, A., Ghodsypour, S.H., O’Brien, C., “A weighted additive fuzzy Multi-objective model for the supplier selection problem under price breaks in a supply chain”. International Journal of Production Economics, 121, 323-332,2009.
[3]. Amid, A., Ghodsypour, S.H., O’Brien, C., “A weighted max-min model for fuzzy multi-objective supplier selection in a supply chain”. International Journal of Production Economics, 131, 139-145,2011.
[4]. Bellman, R. E., Zadeh, L.A., “Decision making in a fuzzy environment”. Management Science 17, 141-164,1970.
[5]. Boran, F. E., Genc, S., Kurt, M., Akay, D., “A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method”. Expert Systems with Applications, 36, 11363-11368.
[6]. Briggs, P., “Vendor assessment for partners in supplyCHAIN”. European Journal of Purchasing & Supply Management 1, 49- 59,1994.
[7]. Chen, C.T., Lin, C.T., Huang S.F., “A fuzzy approach for supplier evaluation and selection in supply chain management”. International Journal of Production Economics, 102, 289- 301,2005.
[8]. Choi, T.Y., Hartley, J.L., “An exploration of supplier selection practices across the supply chain”. Jr. of Op. Mgmt. 14, 333- 343,1996.
[9]. Chou, C. C.,“The Canonical representation of multiplication operation on triangular fuzzy numbers”. Computers and Mathematics with Applications, 45, 1601-1610,2003.
[10]. Deng, Y., Chan, F. T. S., “A new fuzzy dempster MCDM method and its application in supplier selection”. Expert Systems with Applications, 38, 9854-9861,2011.
[11]. Dickson, G.W., “An analysis of vendor selection systems and decisions”. Journal of Purchasing. 2 (1), 5-17,1996.
[12]. Dulmin, R., Mininno, V., “Supplier selection using a multicriteria decision aid method”. Jr of Pur. and Supply Mgmt, 9,177- 187,2003.
[13]. Guneri, A. F., Yucel, A., Ayyildiz, G., “An integrated fuzzy-lp approach for a supplier selection problem in supply chain management”. Expert Systems with Applications, 36, 9223- 9228,2009.
[14]. Kauffman, A., Gupta, M. M., “Introduction of fuzzy arithmetic: Theory and applications”. New York: Van Nostrand Reinhold, 1985.
[15]. Kumar, M., Vrat, P., Shankar, R., “A fuzzy goal programming approach for vendor selection problem in a supply chain”. Computers and Industrial Engineering, 46, 69-85, 2004.
[16]. Kumar, M., Vrat, P., Shankar, R., “A fuzzy programming approach for vendor selection problem in a supply chain”. International Journal of Production Economics 101, 273-285. 2005.
[17]. Zadeh, L.A., “Outline of a new approach to the analysis of complex systems and decision processes”. — IEEE Trans. Syst. Man. Cybern., 3(1), 28–44,1973.
[18]. Lee, H.L., and Billington, C., “Managing supply chain inventory: Pitfalls and opportunities”. Sloan Mgmt.. Rev., 33(3), 65–73, 1992.
[19]. Leberling, H., “On finding compromise solutions in multicriteria problems using the fuzzy min-operator”. Fuzzy Sets and Systems, 6, 105-118, 1980.
[20]. Narasimhan, R., “An Analytic Approach to supplier selection”. Journal of Purchasing and Supply Management, 1, 27-32,1983.
[21]. Ozkok, B. A., Tiryaki, F., “A compensatory fuzzy approach to multi-objective linear supplier selection problem with multipleitem”. Expert Systems with Applications, 38, 11363-11368, 2011.
[22]. Selim, H., Araz, C., Ozakarahan, I., “Collaborative production distribution planning in supply chain: A fuzzy goal programming approach”. Transportation Research Part E .44, 396-419,2006.
[23]. Tiwari, R. N., Dharmar, S., and Rao, J.R., “Fuzzy goal programming- an additive model”. Fuzzy Sets and Systems, 24, 27-34,1986.
[24]. Zadeh, L.A., “The role of fuzzy logic in the management of uncertainty in expert systems”. Fuzzy Sets Syst.,11(3), 199–227, 1983.
[25]. Zimmermann, H. J., “Fuzzy programming and linear programming with several objective functions”. Fuzzy Sets and Systems, 1, 45-55,1978.
[26]. Zimmermann, H. J., “Fuzzy Sets, Decision Making and Expert Systems”. Kluwer Academic Publishers, Boston1987.
[27]. Zimmermann, H.J., “Fuzzy Set Theory and Its Applications”. Boston: Kluwer Academic Publishers, 1991.
Bachelors degree in the field of Computer Applications Master's Degree in the field of Statistics. He has keen interest in the area of data mining, operation research, supply chain modelling, fuzzy systems, Neural networks, and has published several papers in National and International conferences and journals. Dr. Raosaheb Latpate has more than seven years of experience in teaching undergraduate as well as postgraduate students. He has attended several workshops and faculty development programs. He has 7 Research Papers to his credit.
No. of Downloads: 9 | No. of Views: 1197
