Simulation to reallocate supply to committed orders under shortage

References

• Alarcón, F., M. M. E. Alemany, F. Lario, and R. Oltra. 2011. “La Falta de Homogeneidad del Producto (FHP) en las Empresas Cerámicas y su Impacto en la Reasignación de Inventario.” Boletín de la Sociedad Española de Cerámica y Vidrio 50 (1): 49–58. doi:10.3989/cyv.072011.
   Web of Science ®Google Scholar
• Alemany, M. M. E., F. Alarcón, R. Oltra, and F. Lario. 2013a. “Reasignación Óptima del Inventario a Pedidos en Empresas Cerámicas Caracterizadas por la Falta de Homogeneidad en el Producto (FHP).” Boletín de la Sociedad Española de Cerámica y Vidrio 52 (1): 31–41. doi:10.3989/cyv.42013.
   Web of Science ®Google Scholar
• Alemany, M. M. E., H. Grillo, A. Ortiz, and V. S. Fuertes-Miquel. 2015b. “A Fuzzy Model for Shortage Planning Under Uncertainty due to Lack of Homogeneity in Planned Production Lots.” Applied Mathematical Modelling 39 (15): 4463–4481. doi:10.1016/j.apm.2014.12.057.
   Web of Science ®Google Scholar
• Alemany, M. M. E., F. Lario, A. Ortiz, and F. Gómez. 2013b. “Available-To-Promise Modeling for Multi-Plant Manufacturing Characterized by Lack of Homogeneity in the Product: An Illustration of a Ceramic Case.” Applied Mathematical Modelling 37 (5): 3380–3398. doi:10.1016/j.apm.2012.07.022.
   Web of Science ®Google Scholar
• Alemany, M. M. E., A. Ortiz, A. Boza, and V. S. Fuertes-Miquel. 2015a. “A Model-Driven Decision Support System for Reallocation of Supply to Orders Under Uncertainty in Ceramic Companies.” Technological and Economic Development of Economy 21 (4): 596–625. doi: 10.3846/20294913.2015.1055613
   Web of Science ®Google Scholar
• Boza, A., M. M. E. Alemany, F. Alarcón, and L. Cuenca. 2014. “A Model-Driven DSS Architecture for Delivery Management in Collaborative Supply Chains with Lack of Homogeneity in Products.” Production Planning & Control 25 (8): 650–661. doi:10.1080/09537287.2013.798085.
   Web of Science ®Google Scholar
• Campuzano, F., Mula, J. (2011). Supply Chain Simulation: A System Dynamics Approach for Improving Performance. Ed. Springer-Verlag, London.
   Google Scholar
• Campuzano-Bolarin, F., J. Mula, and D. Peidro. 2013. “An Extension to Fuzzy Estimations and System Dynamics for Improving Supply Chains.” International Journal of Production Research 51 (10): 3156–3166. doi:10.1080/00207543.2012.760854.
   Web of Science ®Google Scholar
• Davoli, G, S. A Gallo, M. W Collins, and R Melloni. 2010. “A Stochastic Simulation Approach for Production Scheduling and Investment Planning in the Tile Industry.” International Journal of Engineering, Science and Technology 2 (9): 107–124.
   Google Scholar
• Forrester, J. W. 1961. Industrial Dynamics. Cambridge, Massachusetts: The MIT Press. Massachusetts Institute of Technology.
   Google Scholar
• Framinan, J. M., and R. Leisten. 2010. “Available-To-Promise (ATP) Systems: A Classification and Framework for Analysis.” International Journal of Production Research 48: 3079–3103. doi:10.1080/00207540902810544.
   Web of Science ®Google Scholar
• Georgiadis, P., and C. Michaloudis. 2012. “Real-Time Production Planning and Control System for Job-Shop Manufacturing: A System Dynamics Analysis.” European Journal of Operational Research 216 (1): 94–104. doi:10.1016/j.ejor.2011.07.022.
   Web of Science ®Google Scholar
• Georgiadis, P., and A. Politou. 2013. “Dynamic Drum-Buffer-Rope Approach for Production Planning and Control in Capacitated Flow-Shop Manufacturing Systems.” Computers & Industrial Engineering 65 (4): 689–703. doi:10.1016/j.cie.2013.04.013.
   Web of Science ®Google Scholar
• Grillo, H., M. M. E. Alemany, and A. Ortiz. 2016. “A Review of Mathematical Models for Supporting the Order Promising Process Under Lack of Homogeneity in Product and Other Sources of Uncertainty.” Computers & Industrial Engineering 91: 239–261. doi: 10.1016/j.cie.2015.11.013
   Web of Science ®Google Scholar
• Grillo, H., M.M.E. Alemany, A. Ortiz, and J. Mula. 2018. “A Fuzzy Order Promising Model with Non-Uniform Finished Goods.” International Journal of Fuzzy Systems 20: 187–208. doi:10.1007/s40815-017-0317-y.
   Web of Science ®Google Scholar
• Jeon, S. M., and G. Kim. 2016. “A Survey of Simulation Modeling Techniques in Production Planning and Control (PPC).” Production Planning and Control 27 (5): 360–377. doi:10.1080/09537287.2015.1128010.
   Web of Science ®Google Scholar
• Mula, J., Campuzano, F., Manuel, Díaz-Madroñero, Karpio, K.M. (2013). A System Dynamics Model for the Supply Chain Procurement Transport Problem: Comparing Spreadsheets, Fuzzy Programming and Simulation Approaches. International Journal of Production Research 51 (13): 4087-4104. doi:10.1080/00207543.2013.774487.
   Web of Science ®Google Scholar
• Olhager, J. 2003. “Strategic Positioning of the Order Penetration Point.” International Journal of Production Economics 85 (3): 319–329. doi:10.1016/S0925-5273(03)00119-1.
   Web of Science ®Google Scholar
• Sterman, J. D. 2000. Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston: McGraw-Hill.
   Google Scholar
• Tako, A., and S. Robinson. 2011. “The Application of Discrete Event Simulation and System Dynamics in the Logistics and Supply Chain Context.” Decision Support Systems 52 (4): 802–815. doi:10.1016/j.dss.2011.11.015.
   Web of Science ®Google Scholar