Mathematical programming-based methodology for the evaluation of supply chain collaborative planning scenarios

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Abstract

Nowadays, 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.

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APA

Pérez-Perales, D., Boza, A., Alarcón, F., & Gómez-Gasquet, P. (2024). Mathematical programming-based methodology for the evaluation of supply chain collaborative planning scenarios. Annals of Operations Research, 337(1), 261–312. https://doi.org/10.1007/s10479-024-05917-6

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