Badri, M. A. (1999). Combining the analytic hierarchy process and goal programming for global facility locationallocation problem. International Journal of Production Economics, 62(3), 237-248.
Ben-Tal, A., & Nemirovski, A. (2000). Robust solutions of linear programming problems contaminated with uncertain data. Mathematical programming, 88(3), 411-424.
Bertsimas, D., & Sim, M. (2004). The price of robustness. Operations research, 52(1), 35-53.
Canel, C., & Khumawala, B. M. (1996). A mixed-integer programming approach for the international facilities location problem. International Journal of Operations & Production Management, 16(4), 49-68.
Caniato, F., Golini, R., & Kalchschmidt, M. (2013). The effect of global supply chain configuration on the Eq.ship between supply chain improvement programs and performance. International Journal of Production Economics, 143(2), 285-293.
Chang, C. T., & Chang, C. C. (2000). A linearization method for mixed 0–1 polynomial programs. Computers & Operations Research, 27(10), 1005-1016.
Chopra, S., & Meindl, P. (2007). Supply chain management. Strategy, planning & operation (pp. 265-275).Gabler.
Dubois, D., & Prade, H. (1987). Linear programming with fuzzy data. Analysis of fuzzy information, 3, 241-263.
Farahani, R. Z., Asgari, N., & Davarzani, H. (Eds.). (2009). Supply chain and logistics in national, international and governmental environment: concepts and models. Springer Science & Business Media.
Goh, M., Lim, J. Y., & Meng, F. (2007). A stochastic model for risk management in global supply chain networks. European Journal of Operational Research, 182(1), 164-173.
Gui-xia, Q., Y.-p. ZHANG, W. Jian-guo and P. Yue-hong (2013). "Revenue sharing in dairy industry supply chain-a case study of Hohhot, China." Journal of Integrative Agriculture 12(12): 2300-2309.
Hammami, R., & Frein, Y. (2013). An optimisation model for the design of global multi-echelon
supply chainsunder lead time constraints. International Journal of Production Research, 51(9), 2760-2775.
Hammami, R., & Frein, Y. (2014). Redesign of global supply chains with integration of transfer pricing: Mathematical modeling and managerial insights. International Journal of Production Economics, 158, 267-277.
Heilpern, S. (1992). The expected value of a fuzzy number. Fuzzy sets and Systems, 47(1), 81-86.
Hodder, J. E., & Dincer, M. C. (1986). A multifactor model for international plant location and financing under uncertainty. Computers & Operations Research, 13(5), 601-609.
Hodder, J. E., & Jucker, J. V. (1982, December). Plant location modeling for the multinational firm. In Proceedings of the Academy of International Business Conference on the Asia-Pacific Dimension of International Business (pp. 248-258). Honolulu, HI: AIB.
Iakovou, E., Vlachos, D., Achillas, C., & Anastasiadis, F. (2012). A methodological framework for the design of green supply chains for the agrifood sector. Working paper.
Jamalnia, A., Mahdiraji, H. A., Sadeghi, M. R., Hajiagha, S. H. R., & Feili, A. (2014). An integrated fuzzy QFD and fuzzy goal programming approach for global facility location-allocation problem. International Journal of Information Technology & Decision Making, 13(02), 263-290.
Leung, S. C., Tsang, S. O., Ng, W. L., & Wu, Y. (2007). A robust optimization model for multi-site production planning problem in an uncertain environment. European Journal of Operational Research, 181(1), 224-238.
Meixell, M. J., & Gargeya, V. B. (2005). Global supply chain design: A literature review and critique.Transportation Research Part E: Logistics and Transportation Review, 41(6), 531-550.
Meepetchdee, Y., & Shah, N. (2007). Logistical network design with robustness and complexity considerations. International Journal of Physical Distribution & Logistics Management, 37(3), 201-222.
Mulvey, J. M., Vanderbei, R. J., & Zenios, S. A. (1995). Robust optimization of large-scale systems. Operations research, 43(2), 264-281
Munson, C. L., & Rosenblatt, M. J. (1997). The impact of local content rules on global sourcing decisions. Production and Operations Management, 6(3), 277-290.
Perron, S., Hansen, P., Le Digabel, S., & Mladenović, N. (2010). Exact and heuristic solutions of the global supplychain problem with transfer pricing. European Journal of Operational Research, 202(3), 864-879.
Pishvaee, M. S., Razmi, J., & Torabi, S. A. (2012). Robust possibilistic programming for socially responsible supply chain network design: A new approach. Fuzzy sets and systems, 206, 1-20.
Ramezani, M., Bashiri, M., & Tavakkoli-Moghaddam, R. (2013). A new multi-objective stochastic model for a forward/reverse logistic network design with responsiveness and quality level. Applied Mathematical Modelling, 37(1), 328-344.
Sheu, J. B., & Lin, A. Y. S. (2012). Hierarchical facility network planning model for global logistics network configurations. Applied Mathematical Modelling, 36(7), 3053-3066.
Shunko, M. A. S. H. A., & Gavirneni, S. R. I. N. A. G. E. S. H. (2007). Role of transfer prices in global supply chains with random demands. Journal of Industrial and Management Optimization, 3(1), 99.
Syam, S. S. (1997). A model for the capacitated p-facility location problem in global
environments. Computers & operations research, 24(11), 1005-1016.
Taylor, D. H. (1997). Global cases in logistics and supply chain management. Cengage Learning EMEA.
Tsolakis, N. K., Keramydas, C. A., Toka, A. K., Aidonis, D. A., & Iakovou, E. T. (2014). Agri-food supply chain management: a comprehensive hierarchical decision-making framework and a critical taxonomy. Biosystems Engineering, 120, 47–64.
Yager, R. R. (1981). A procedure for ordering fuzzy subsets of the unit interval. Information sciences, 24(2), 143-161.