How to cite this paper
Fera, M., Fruggiero, F., Lambiase, A., Macchiaroli, R & Miranda, S. (2017). The role of uncertainty in supply chains under dynamic modeling.International Journal of Industrial Engineering Computations , 8(1), 119-140.
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Bhagwat, R., & Sharma, M. K. (2007). Performance measurement of supply chain management: A balanced scorecard approach. Computers & Industrial Engineering, 53(1), 43-62.
Beaudoin, D., LeBel, L., & Frayret, J. M. (2006). Tactical supply chain planning in the forest products industry through optimization and scenario-based analysis. Canadian Journal of Forest Research, 37(1), 128-140.
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Bhaskaran, S. (1998). Simulation analysis of a manufacturing supply chain.Decision Sciences, 29(3), 633.
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Borgonovo, E., & Peccati, L. (2004). Sensitivity analysis in investment project evaluation. International Journal of Production Economics, 90(1), 17-25.
Bowersox, D. J., & Calantone, R. J. (1998). Global logistics. Journal of International Marketing, 83-93.
Cachon, G. P., & Lariviere, M. A. (2001). Contracting to assure supply: How to share demand forecasts in a supply chain. Management science, 47(5), 629-646.
Carlsson, C., & Fullér, R. (2002). A fuzzy approach to taming the bullwhip effect. In Advances in Computational Intelligence and Learning (pp. 247-262). Springer Netherlands.
Campuzano, F., Mula, J., & Peidro, D. (2010). Fuzzy estimations and system dynamics for improving supply chains. Fuzzy Sets and Systems, 161(11), 1530-1542.
Chen, C. T., Lin, C. T., & Huang, S. F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal of Production Economics, 102(2), 289-301.
Chen, P. Y. (2012). The investment strategies for a dynamic supply chain under stochastic demands. International Journal of Production Economics, 139(1), 80-89.
Cheung, K. L., & Lee, H. L. (2002). The inventory benefit of shipment coordination and stock rebalancing in a supply chain. Management Science,48(2), 300-306.
Chiang, W. Y. K., Chhajed, D., & Hess, J. D. (2003). Direct marketing, indirect profits: A strategic analysis of dual-channel supply-chain design. Management science, 49(1), 1-20.
Colicchia C. & Strozzi, F. (2012). Supply chain risk management: A new methodology for a systematic. Supply Chain Management: An International Journal,17(4), 403 - 418.
Chauhan, S. S., Dolgui, A., & Proth, J. M. (2009). A continuous model for supply planning of assembly systems with stochastic component procurement times. International Journal of Production Economics, 120(2), 411-417.
Chanas, S., Delgado, M., Verdegay, J. L., & Vila, M. A. (1993). Interval and fuzzy extensions of classical transportation problems. Transportation Planning and Technology, 17(2), 203-218.
Chen, S. P., & Chang, P. C. (2006). A mathematical programming approach to supply chain models with fuzzy parameters. Engineering Optimization, 38(6), 647-669.
Efendigil, T., & Önüt, S. (2012). An integration methodology based on fuzzy inference systems and neural approaches for multi-stage supply-chains.Computers & Industrial Engineering, 62(2), 554-569.
Elofson, G., & Robinson, W. N. (2007). Collective customer collaboration impacts on supply-chain performance. International Journal of Production Research, 45(11), 2567-2594.
Eppen, G. D., & Iyer, A. V. (1997). Backup agreements in fashion buying—the value of upstream flexibility. Management Science, 43(11), 1469-1484.
Esper, T. L., & Williams, L. R. (2003). The value of collaborative transportation management (CTM): its relationship to CPFR and information technology.Transportation Journal, 42(4), 55-65.
European Commission, (2003). Commission Recommendation concerning the definition of micro, small and medium -sized enterprises, s.l.: Official Journakl of the European Union.
Esmaeili, M., Aryanezhad, M. B., & Zeephongsekul, P. (2009). A game theory approach in seller–buyer supply chain. European Journal of Operational Research, 195(2), 442-448.
Esmaeili, M., Aryanezhad, M. B., & Zeephongsekul, P. (2009). A game theory approach in seller–buyer supply chain. European Journal of Operational Research, 195(2), 442-448.
Feng, Y. (2012). System Dynamics Modeling for Supply Chain Information Sharing. Physics Procedia, 25, 1463 – 1469 .
Fisher, M. L., Hammond, J. H., Obermeyer, W. R., & Raman, A. (1994). Making supply meet demand in an uncertain world. Harvard Business Review, 72, 83-83.
Fugate, B., Sahin, F., & Mentzer, J. T. (2006). Supply chain management coordination mechanisms. Journal of Business Logistics, 27(2), 129-161.
Giannoccaro, I., Pontrandolfo, P., & Scozzi, B. (2003). A fuzzy echelon approach for inventory management in supply chains. European Journal of Operational Research, 149(1), 185-196.
Grubbström, R. W., & Kingsman, B. G. (2004). Ordering and inventory policies for step changes in the unit item cost: a discounted cash flow approach.Management science, 50(2), 253-267.
Grubbström, R. W., & Thorstenson, A. (1986). Evaluation of capital costs in a multi-level inventory system by means of the annuity stream principle.European Journal of Operational Research, 24(1), 136-145.
Hameri, A. & Nikkola, J., 2001. Order penetration point in the paper supply chain. Paperi Ja Puu-Paper and Timber, 83(4), 299-302.
Harris, F. M. (1913). How Many Parts to Make at Once. Factory, The Magazine of Management10:2, 135–136, 152. Reprinted in Operations Research 38:6 (1990), pp. 947-950.
He, M., Leung, H. F., & Jennings, N. R. (2003). A fuzzy-logic based bidding strategy for autonomous agents in continuous double auctions. IEEE Transactions on Knowledge and data Engineering, 15(6), 1345-1363.
Henning, G. P. (2009). Production scheduling in the process industries: current trends, emerging challenges and opportunities. Computer Aided Chemical Engineering, 27, 23-28.
Hoffman, J. M., Shah, N. D., Vermeulen, L. C., Schumock, G. T., Grim, P., Hunkler, R. J., & Hontz, K. M. (2006). Projecting future drug expenditures-2006. American Journal of Health-system Pharmacy, 63(2), 123-138.
Hülsmann, M., Grapp, J., & Li, Y. (2008). Strategic adaptivity in global supply chains—competitive advantage by autonomous cooperation. International Journal of Production Economics, 114(1), 14-26.
Iannone, R., Miranda, S., & Riemma, S. (2007). Supply chain distributed simulation: An efficient architecture for multi-model synchronization. Simulation Modelling Practice and Theory, 15(3), 221-236.
Iannone, R., Miranda, S., Riemma, S., Sarno, D. (2010), A model for vendor selection and dynamic evaluation, IFIP WG 5.7 International Conference on Advances in Production Management Systems: New Challenges, New Approaches, APMS 2009, Bordeaux. IFIP Advances in Information and Communication Technology, (338) AICT, 283-290.
Iannone, R., Martino, G., Miranda, S., & Riemma, S. (2015). Modeling fashion retail supply chain through causal loop diagram. IFAC-PapersOnLine, 48(3), 1290-1295.
Jiang, G., Hu, B., & Wang, Y. (2010). Agent-based simulation of competitive and collaborative mechanisms for mobile service chains. Information Sciences,180(2), 225-240.
Julien, B. (1994). An extension to possibilistic linear-programming. Fuzzy Sets and Systems, 64, 194-206.
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