Companies goal is keeping competitive and achieving significant
profits by meeting all of their customers’ demands. For this
sake, an effective production planning which is suitable for the company
is required. In this context, we are interested by the integrated optimization
of aggregate production planning and disaggregate production
planning in order to guarantee feasibility and consistency across
planning levels. The main contribution of this paper lies in using the
integrated model’s output as an input to the scheduling model. Computational
tests conducted first considering data from literature to mainly
test the sensitivity of the three production planning models and then
for the integrated model and the scheduling one. It was illustrated how
each planning model is impacted by the parameter variations, emphasizing
the integration’s robustness in preserving operational stability.
Then, real data from a pharmaceutical company was used for only
the integrated model and the scheduling one. It was shown how total
weighted tardiness was minimized by 2 weeks compared to non integrated
models. Finally, it should be mentioned that verification constraints
established verification constraints between the two planning
levels leads to a cost-effective solution for multi-product, multi-stage
batch production environments.
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