The datasets presented here were partially used in “Formulation and MIP-heuristics for the lot sizing and scheduling problem with temporal cleanings” (Toscano, A.,? Ferreira, D., Morabito, R., Computers & Chemical Engineering) , in “A decomposition heuristic to solve the two-stage lot sizing and scheduling problem with temporal cleaning” (Toscano, A., Ferreira, D., Morabito, R., Flexible Services and Manufacturing Journal) , and in “A heuristic approach to optimize the production scheduling of fruit-based beverages” (Toscano et?al., Gest?o & Produ??o, 2020) . In fruit-based production processes, there are two production stages: preparation tanks and production lines. This production process has some process-specific characteristics, such as temporal cleanings and synchrony between the two production stages, which make optimized production planning and scheduling even more difficult. Thus, some papers in the literature have proposed different methods to solve this problem. To the best of our knowledge, there are no standard datasets used by researchers in the literature to verify the accuracy and performance of proposed methods or to be a benchmark for other researchers considering this problem. The authors have been using small data sets that do not satisfactorily represent different scenarios of production. Since the demand in the beverage sector is seasonal, a wide range of scenarios enables us to evaluate the effectiveness of the proposed methods in the scientific literature in solving real scenarios of the problem. The datasets presented here include data based on real data collected from five beverage companies. We presented four datasets that are specifically constructed assuming a scenario of restricted capacity and balanced costs.
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