Document Type : Research Paper



Appropriate management of supply chain is one of the issues facing economic firms that affect all the organizational activities in order to produce the goods and provide the services. Consequently Supplier selection due to involvement of various qualitative and quantitative criteria such as quality, price, flexibility and delivery times is very difficult and complex and requires accurate and appropriate tools. On the other hand today's competitive environment due to its variable nature, has added the uncertainty and ambiguity in decision-making. The problem of supplier selection is not an exception as well and it seems suitable to use the robust optimization methods in such circumstances. The mentioned method is used in this research with the goal of supplier selecting and determining the amount order of products considering all restrictions in order to minimize the costs and maximize the utility of purchase in the condition of uncertainty. In this paper, a multi-objective deterministic model is presented to solve the problem, and then the deterministic model is converted to the robust model using the scenario-based robust method and then is solved using the LP metric method so optimal amount of order is obtained from each of suppliers at any period. To determine the weight of each of suppliers, Analytical Hierarchy Process (AHP) is used as well.


یحییزاده اندواری یلدا، الفت ،) لعیا، امیری مقصود ) 9354 انتخاب تامین کننده و تعیین مقدار
سفارش در شرایط عدم قطعیت، پایان نامه کارشناسی ارشد مدیریت صنعتی . دانشکده حسابداری و
مدیریت دانشگاه علامه طباطبایی.
Amid, A., Ghodsypour, S.H., O’Br , C., 2009. w gh a v fuzzy multiobjective model for supplier selection in a supply chain under price breaks. International Journal of Production Economics 121, 323–332.
Chang, P. C., Lin, Y. K., (2010), "New challenges and opportunities in flexible and robust supply chain forecasting systems", International Journal of Production Economics, vol.127,pp.453-456.
D B r, L., La r , E., rla h , P., (2001). “ r v w f h pp r g ppl r l ” E r p a J r al f Purchasing & Supply Management, Vol. 7,Pp. 75-89
Dickson, G.W., 1966. An analysis of vendor selection systems and decisions. Journal of Purchasing 2 (1), 5–17.
Ghodsypour, S.H. and O'Brien, C., (1998). "A decision support system for suppleir selection using integrated analytic hierarchy process and linear programing", I.J. of Production Economics, Vol. 56-57, pp. 199-212..
Gh p r, S.H., O’Br , C., 2001. h al f l g supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraint. International Journal of Production Economics 73, 15–27.
Klibi, W., Martel, A., Guitouni, A., (2010). "The design of robust value-creating supply chain networks: A critical review", European Journal of Operational Research, Vol. 203, pp. 283–293.

Kumar,m.,Vart,p.,Shankar,p.,2004. A fuzzy goal programming approach for Supplier selection problem in a supply chain. Computer and industrial engineering, 46, 69-85.
Lai, K.K., Wang, M., Liang, L. , Wu, Y., (2007). " A stochastic approach to professional services f r ’r v p a ". E r p a Journal of Operational Research, Vol. 182, pp. 971–982.
Leung, S.C.H., Tsang, S.O.S., Ng, W.L. , Wu, Y., (2007). " A robust optimization model for multisite production planning problem in an uncertain environment". European Journal of Operational Research, Vol. 181, pp. 224–238.
Mirzapour Al-e-hashem, S.M.J. , Malekly, H., Aryanezhad, M.B., (2011). " A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty" , International Journal of Production Economics , vol. 134, pp. 28–42.
Mulvey, J.M., Vanderbei, R.J., Zenios, S.A., (1995). "Robust optimization of large scale systems", Oper. Res. Lett, Vol. 43 (2), pp. 264–281.
Mulvey, J.M., Ruszczynski, A., 1995. A new scenario decomposition method for large-scale stochastic optimization. Operations Research 43, 477–490.
Nama, S.H., Vitton, J., Kurata, H.,(2011). "Robust supply base management: Determining the optimal number of suppliers utilized by contractors", Int. J. Production Economics, vol.143,pp.333-343.
Pan, F., Nagi, R., (2010). "Robust supply chain design under uncertain demand in agile manufacturing", Computers & Operations Research, Vol. 37, pp. 668-683.

Pishvaee M. S., Rabbani M., Torabi S. A., (2011). "A robust optimization approach to closed-loop supply chain network design under uncertainty", Applied Mathematical Modelling, Vol. 35, pp. 637–649.
Reiner, G., Trcka, M., (2004), "Customized supply chain design: Problems and alternatives for a production company in the food industry: A simulation based analysis", Int. J. Production Economics,Vol. 89, pp. 217-229.
Sahinidis, N.V., 2004. Optimization under uncertainty: state-of-the-art and oppor- tunities. Computers and Chemical Engineering 28 (6–7), 971–983.
Soyster, A.L., (1973). "Convex programming with set-inclusive constraints: Applications to inexact linear programming". Operations Research, Vol. 21, pp. 1154–1157.
Van Landeghem, H.V., Vanmaele, H., (2002). " Robust planning: a new paradigm for demand chain planning", Journal of Operations Management, Vol. 20, pp. 769–783.
Weber, C.A., Current, J.R., Benton, W.C., 1991. Vendor selection criteria and methods. European Journal of Operational Research 50, 2–18.
Yu, C.S., Li, H.L., 2000. A robust optimization model for stochastic logistic problems. International Journal of Production Economics 64, 385–397.
Zhang, Zho., Lei, J., Cao, N., To, K. and Ng. K., (2004). "Evolution oF supplier selection criteria and methods", (, pp. 1-19. [des2004].