Simulação para a otimização da colheita da cana-de-açúcar
Ano de defesa: | 2015 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Tese |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Estadual Paulista (Unesp)
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Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | http://hdl.handle.net/11449/139399 http://www.athena.biblioteca.unesp.br/exlibris/bd/cathedra/18-05-2016/000865102.pdf |
Resumo: | Sugarcane was introduced in Brazil in the colonial period and it has become one of the most important crop 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 sugarcane management are large and tools to aid in decision making, management optimization and estimate are necessary. Within that context it is discussed, in this paper, a study of the sugarcane 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 managers plants in decision-making in planning the harvest of sugarcane |