This paper proposes a scenario-based two-stage stochasticprogramming model with recourse for master production scheduling under demand uncertainty. We integrate the model into a hierarchical production planning and c...
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This paper proposes a scenario-based two-stage stochasticprogramming model with recourse for master production scheduling under demand uncertainty. We integrate the model into a hierarchical production planning and control system that is common in industrial practice. To reduce the problem of the disaggregation of the master production schedule, we use a relatively low aggregation level (compared to other work on stochasticprogramming for production planning). Consequently, we must consider many more scenarios to model demand uncertainty. Additionally, we modify standard modelling approaches for stochasticprogramming because they lead to the occurrence of many infeasible problems due to rolling planning horizons and interdependencies between master production scheduling and successive planning levels. To evaluate the performance of the proposed models, we generate a customer order arrival process, execute production planning in a rolling horizon environment and simulate the realisation of the planning results. In our experiments, the tardiness of customer orders can be nearly eliminated by the use of the proposed stochasticprogramming model at the cost of increasing inventory levels and using additional capacity.
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