Integrated planning for planting and harvesting sugarcane and energy-cane for the production of sucrose and energy

• Autor(a) principal: Poltroniere, Sonia Cristina [UNESP]
• Data de Publicação: 2021
• Outros Autores: Filho, Angelo Aliano, Caversan, Amanda Suellen [UNESP], Balbo, Antonio Roberto [UNESP], Florentino, Helenice de Oliveira [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1016/j.compag.2020.105956; http://hdl.handle.net/11449/210751
• topic: Sugarcane; Energy-cane; Mathematical optimization; Relax-and-fix; Fix-and-optimize

The main products obtained from sugarcane for the global market are sugar, ethanol and energy. Although the demand for these products is high, in Brazil there is no longer space to expand sugarcane cultivation due to other important food crops and environmental protection areas. Therefore, current research seeks ways to increase sugarcane productivity without expanding the planted area. Consequently, a type of cane with higher concentration of fiber has been developed and cultivated called energy-cane. This cane type has more fiber than sucrose in its composition, which makes it better for producing energy and ethanol and inappropriate for sugar production. To meet the demands for these three products, both energy-cane and sugarcane are needed, making the planning and decision-making more difficult in the energy-sugar sector. In this context, a mixed integer linear optimization model for the integrated planning of the planting and harvesting of sugarcane and energy-cane for a sugar-energy plant is proposed to determine an optimized planting and harvesting schedule, that aims to maximize the sucrose and fiber production in the cane fields. The model takes into account a flexible harvest period to meet the demands of the consumer market and respect the operational constraints of the company, which can cause variations in productivity. To solve real-life instances where exact methods fail, a heuristic based on the relax-and-fix and fix-and-optimize concepts is proposed. Numerical experiences with random instances were generated to test both the model and the heuristic. Feasible solutions with an error close to 1% were obtained, consuming one tenth of the CPU time, on average. Thus, the mathematical model and the heuristic method developed have great potential to support decision-making in sugarcane and energy-cane production planning.