Hierarchical Approach for Production Planning and Scheduling under Uncertainty

In this paper, production planning and scheduling problems are addressed through a hierarchical framework. The planning problem aggregates orders in the planning period and considers uncertainty utilizing a multi-stage stochastic programming formulation where three stages are considered with increasing level of uncertainty. The planning model includes material balances and time horizon constraints involving a sequence factor to reflect the recipe complexity in the planning model. The production for the current stage is then provided to the scheduling problem, which is solved using an existing continuous-time formulation. In order to reduce the computational complexity of the overall approach, a Lagrangean decomposition method is utilized and the general framework is implemented based on rolling horizon strategy.