Mathematical Programming Approaches for Stable Tactical and Operational Planning in Supply Chain and APS Context

André Thomas (1) , Patrick Genin (2) , Samir Lamouri (2)

1 CRAN - Centre de Recherche en Automatique de Nancy
2 LISMMA - Laboratoire d'Ingénierie des Systèmes Mécaniques et des MAtériaux

The economic context leads companies to answer quickly to the unpredictable changing customer demands. Advanced Planning Systems (APS) are useful tools to set up quickly Sales and Operations Planning (SOP) and Master Production Schedules (MPS). The problem is to obtain stable plans and schedules in spite of the unstable demand. In this paper, we propose a special procedure based on mathematical programming modelling to obtain stable MPS on the basis of a stable and robust SOP. The MPS process is built in two steps. The first leads to implement a SOP with a “reference plan policy”. In the second step, SOP (quantity per family per month) is broken down into quantity of finished products per month, and then, into quantity of finished products per week (MPS). As we observe unstable MPS using Bitran and Hax procedure (1981), we propose a demand levelling stochastic treatment leading to better stability.

Mots clés: Hierarchical Production Planning; Disaggregation; Linear optimisation; Nonlinear Optimisation; Robustness; Stability

Domaines: Autre

André Thomas, Patrick Genin, Samir Lamouri. Mathematical Programming Approaches for Stable Tactical and Operational Planning in Supply Chain and APS Context. Journal of Decision Systems, 2008, 17 (3), pp.425-455. ⟨hal-00325681⟩