Agrawal, V. and & S. Seshadri, S. (2000). Risk intermediation in supply chains. IIE Transactions, 32, :819-831.
Alonso-Ayuso, A., et al. (2003). An approach for strategic supply chain planning under uncertainty based on stochastic 0-1 programming. Journal of Global Optimization, 26: 97-124.
Amid, S. H. & Ghodsypour, C. (2006). O’Brien, Fuzzy multi objective linear model for supplier selection in a supply chain. International Journal of Production Economics, 104: 394 – 407.
Applequist, G. E., Pekny, J. F., & Reklaitis, G. V. (2000). Risk and uncertainty in managing chemical manufacturing supply chains. Comput. Chem. Eng, 24: 2211–2222.
Azaron, A., Brown, K. N., Tarim, S. A. & M. Modarres. (2008). A multi-objective stochastic programming approach for supply chain design considering risk. International Journal of Production Economics, 116: 129-138.
Bai, D., Carpenter, T. & Mulvey, J. (1997). Making a case for robust optimization models. Management Science, 43(7): 895-907.
Beamon, B. M. (1998). Supply chain design and analysis: models and methods. International Journal of Production Economics, 55: 281-294.
Ben-Tal, A. & Nemirovski, A. (2002). Robust optimization methodology and applications. Mathematical Programming Series B, 92: 453-480.
Chan, F. T. S. & Chan, H. K. (2005). Simulation modeling for comparative evaluation of supply chain management strategies. International Journal of Advanced Manufacturing Technology, 25: 998-1006.
Chang, Y. & Harris, M. (2001). Supply chain modeling using simulation. International Journal of Simulation: Systems, Science & Technology, 2(1), 24–30.
Chopra, S., Reinhardt, G. & Mohan, U. (2007). The importance of decoupling recurrent and disruptions risks in a supply chain. Naval Research Logistics, 54(5): 544-555.
Deleris, L. A. & Erhun, F. (2005). Risk management in supply networks using Monte-Carlo simulation. Proceeding of the 2005 Winter Simulation Conference, 1643-1649.
Deshpande, P., Shukla, D., Tiwari, M. (2011). Fuzzy goal programming for inventory management: a bacterial foraging approach. European Journal of Operational Research, 212: 325–336.
E. Aghezzaf. (2005). Capacity planning and warehouse location in supply chains with uncertain demands, J. Oper. Res. Soc. 56: 453–462.
Eppen, G. D., Martin, R. K. & Schrage, L. (1989). A Scenario approach to capacity planning. Operations Research, 37(4): 527-527.
Greenberg, H. J. & Morrison, T. (2008). Robust optimization. In A. R. Ravindran (Ed.), Operations Research and Management Science Handbook, CRC Press. Boca Raton, FL.
Guillén, G., et al. (2005). Multiobjective supply chain design under uncertainty, Chemical Engineering Science, 60: 1535-1553.
Gunasekaran, A., Patel, C. & McGaughey, R. E. (2004). A framework for supply chain performance measurement. International Journal of Production Economics, 87(3): 333– 347.
Gupta, A. & Maranas, C. D. (2003). Managing demand uncertainty in supply chain planning. Computers and Chemical Engineering, 27: 1219-1227.
Hax, A. C. (1974). A comment on the distribution system simulator. Management Science, 21(2): 233-236.
Huang, G. Q., Lau, J. S. K. & Mak, K. L. (2003). The impacts of sharing production information on supply chain dynamics: a review of the literature. International Journal of Production Research, 41(7): 1483–1517.
Kahraman, C., Cebeci, U., & Ruan, D. (2004). Multi-attribute comparison of catering service companies using fuzzy AHP: the case of Turkey. International Journal of Production Economics, 87: 171-184.
Karimi Dastjerd. D., Akbari Jokar, M. & Feizabadi, J. (2009). Developing a Configuration for Classifying Supply Chains Based on RBV in Automotive Industry. Journal of industrial management, (1)2: 121-138. (In Persian)
Leung, S. C. H. & Wu, Y. (2004). A robust optimization model for stochastic aggregate production planning. Production Planning and Control, 15(5): 502-514.
Leung, S. C. H., Wu, Y., & Lai, K. K. (2006). A stochastic programming approach for multi-site aggregate production planning. Journal of the Operational Research Society, 57: 123-132.
Melachrinoudis, E. (1999). Bicriteria location of a semi-obnoxious facility. Computers & Industrial Engineering, 37: 581-593.
Mele, F. D., Guillén, G. Espuña, A. & Puigjaner, L. (2007). Anagent-based approach for supply chain retrofitting under uncertainty. Computer and Chemical Engineering, 31: 722-735.
Min, H. & Melachrinoudis, E. (1999). The relocation of a hybrid manufacturing/ distribution facility from supply chain perspectives: a case study. Omega, 27: 75-85.
Mulvey, J. M., Vanderbei, R. J. & Zenios, S. A. (1995). Robust optimization of large-scale systems. Operations Research, 43(2): 264-281.
Peidro, D., Mula, J., Poler, R. l., Lario, F. C. (2009). Quantitative models for supply chain planning under uncertainty: a review. The International Journal of Advanced Manufacturing Technology, 43(3/4): 400–420.
Ruiz-Femenia, R., Guille´n-Gosa´lbez, G., Jime´nez, L. & Caballero, J. A. (2013). Multi objective optimization of environ mentally conscious chemical supply chains under demand uncertainty. Chemical Engineering Science, 95: 1 –11
Sadeghi Moghadam, M. R., Soroush, M., Momeni, Nalchigar, (2009). integrated planning, and schedule production and distribution supply chain with employing genetic algorithm. Journal of industrial management. 2(1): 88-71. (In Persian)
Santoso, T., Ahmed, S., Goetschalckx, M. & A. Shapiro (2005). A stochastic programming approach for supply chain network design under uncertainty. European Journal of Operational Research, 167: 96-115.
Sarmad, Z., Bazaegan, A. & Hejazi, E. (2004 ), Research Methodologies in Behavioral Sciences, Agah Publications. Tehran. (In Persian)
Shapiro. (2000). Modeling supply chain, Duxbury Press.
Shapiro, A . (2006). Worst-case distribution a nalysis of stochastic programs. Math. Program, Ser. B 107: 91–96.
Sodhi, M. (2003). How to do strategic supply chain planning. Sloan Management Review, 45(1): 69–75.
Surana, A., Kumara, S., Greaves, M. & Raghavan, N. (2005). Supply chain networks: a complex adaptive system perspective. International Journal of Production Research, 43(20): 4235–4265.
Tomlin, B. (2006). On the value of mitigation and contingency strategies for managing supply chain disruption risks. Management Science, 52(5):
639-657.
Tsiakis, P., Shah, N., & Pantelides, C. C. (2001). Design of multi-echelon supply chain networks under demand uncertainty. Industrial & Engineering Chemical Research, 40: 3585-3604.
Wu, Y. (2006). Robust optimization applied to uncertain production loading problems with import quota limits under the global supply chain management environment. International Journal of Production Research, 44(5): 849-882.
Xu, J., Huang, X. & Yan, N. (2007). A multi-objective robust operation model for electronic market enabled supply chain with uncertain demands. Journal of Systems Science and Systems Engineering, 16(1): 74-87.
Xie, Y., Petrovic, D. & Burnham, K. (2006). A heuristic procedure f or the two-level control of serial supply chains under fuzzy customer demand. International Journal of Production Economics, 102: 37 – 50.
Yu, C. S. & Li, H. L. (2000). A robust optimization model for stochastic logistic problems. International Journal of Production Economics, 64: 385-397.
)