Mixed integer programming models for sugarcane harvesting and processing planning

This work presents a comparative analysis between two formulations of mixed integer linear programming for the integrated planning of sugarcane harvesting and processing, meeting the demands of sugar, bioethanol and electricity. Model 1 minimizes the costs of moving the harvesting fronts between plots, while Model 2 incorporates penalties for deviations from the peak of sugarcane maturation. Both formulations consider the sequencing of the harvest fronts, respecting capacity restrictions and meeting demands. Experiments were carried out in 30 instances, varying the number of plots, harvesting fronts and periods of the planning horizon. The average GAP, computational time and harvest plans are analyzed. The results show that the inclusion of penalties for deviations from the peak of maturation generates more realistic plans aligned with the quality of the raw material, with the potential to reduce operating costs in the sugar-energy chain.