Abstract
AbstractNowadays, supply chain (SC) decentralised decision making is the most usual situation in SC operations planning. In this context, different companies can collaboratively plan to achieve a certain level of individual and SC performance. However in many cases, there is reluctance to collaborate because it is not known a priori which benefits will be reported. This paper aims to develop a mathematical programming-based methodology for the evaluation of different supply chain collaborative planning scenarios (MPM-SC-CP). It is assumed that different SC decision centres (DCs) make decisions based on mixed and integer linear programming models. Two main inputs feed the proposed MPM-SC-CP, a framework and associated methodology that support the integrated conceptual and analytical modeling of the SC-CP process in which several DCs make decisions according to spatio-temporal integration. Finally, an application to a real ceramic SC was conducted.
Funder
Universitat Politècnica de València
Publisher
Springer Science and Business Media LLC
Reference84 articles.
1. Acar, Y., & Atadeniz, S. N. (2015). Comparison of integrated and local planning approaches for the supply network of a globally-dispersed enterprise. International Journal of Production Economics, 167, 204–219. https://doi.org/10.1016/j.ijpe.2015.05.028
2. Alarcón, Faustino, Francisco-Cruz Lario Esteban, Andrés Boza, and David Pérez Perales. 2007. “Propuesta de Marco Conceptual Para El Modelado Del Proceso de Planificación Colaborativa de Operaciones En Contextos de Redes de Suministro/Distribución (RdS/D).” In: Proceedings of I International Conference on Industrial Engineering and Industrial Management, pp. 6–7.
3. Albrecht, M., & Stadtler, H. (2015). Coordinating decentralized linear programs by exchange of primal information. European Journal of Operational Research, 247(3), 788–796. https://doi.org/10.1016/j.ejor.2015.06.045
4. Alemany, M. M. E., Alarcón, F., Lario, F. C., & Boj, J. J. (2011). An application to support the temporal and spatial distributed decision-making process in supply chain collaborative planning. Computers in Industry, 62(5), 519–540. https://doi.org/10.1016/j.compind.2011.02.002
5. Alemany, M. M. E., Alarcón, F., Ortiz, A., & Lario, F. C. (2008). Order promising process for extended collaborative selling chain. Production Planning and Control, 19(2), 105–131. https://doi.org/10.1080/09537280801896011