Simulação para a otimização da colheita da cana-de-açúcar

• Autor(a) principal: Nervis, Jonis Jecks
• Data de Publicação: 2017
• Outros Autores: Florentino, Helenice de Oliveira, Cantane, Daniela Renata, Ramos, Rômulo Pimentel, Isler, Paulo Roberto
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Institucional da UFLA
• Texto Completo: http://repositorio.ufla.br/jspui/handle/1/13989
• topic: Algorítmo genético; Problemas combinatoriais; Cana-da-açúcar - Colheita; Otimização da colheita; Genetic algorithm; Combinatorial problems; Sugarcane - Management; Planning harvest

Sugar cane was introduced in Brazil in the colonial period and it has become one of the most important crops for the Brazilian economy. Brazil is not only the largest sugarcane producer, but it is also the first in sugar production and the second in ethanol production and, increasingly, it has been conquering the international market with the biofuel use as an alternative energy. This position has been achieved due to accelerated growth in the last years and it has contributed to the emergence of issues related to logistical transport production process, management and decision-making. The problems caused by this situation to the sugar cane management are large and tools to aid in decision-making, management optimization and estimate are necessary. Within this context, it is discussed, in this paper, a study of the sugar cane management harvest in the mills, proposing a methodology to assist in sugarcane harvest planning in order to maximize the POL in sugarcane, sugarcane productivity and respect the restrictions imposed by the mill. The optimization process was accomplished using GA, heuristic used in large combinatorial problems with computational complexity. Periods of harvesting in stands which belong to a mill were planned and the highest productivity was achieved in a four-year planning. The results are presented and discussed at the end of this study, showing that this approach is an important tool to aid agricultural managers in decision-making in planning the harvest of sugar cane.