Modelagem e otimização da produção em usinas de açúcar e álcool

• Autor(a) principal: Lazzarini, Camilla Miguel Carrara
• Data de Publicação: 2012
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UFU
• Texto Completo: https://repositorio.ufu.br/handle/123456789/14719; https://doi.org/10.14393/ufu.te.2012.87
• topic: Otimização; Usinas de cana-de-açúcar; Operações de transporte; Planejamento agregado da produção; Açúcar - Usinas; Planejamento da produção; Optimization; Sugarcane mills; Transport operations; Planning aggregate production; CNPQ::ENGENHARIAS::ENGENHARIA MECANICA

The integration of agricultural and industrial operations through the use of logistics systems is adopted by companies related to the sugar cane industry as a competitive strategy to improve the operational efficiency of sugarcane mills. The objective of this work is to develop two models that are able to support decisions in a sugar and alcohol milling company. The first presents the optimum equipment sizing of own fleet and/or outsourced fleet available in the mills. The second model considers the aggregate production planning to support key decisions involved in production planning and control process of sugar and alcohol milling company. So, the first part deals with model that represents the transportation system of suppliers cutting fronts from the mills. In the second part is developed a mathematical model of process selection and sizing production lots to represent the production process of sugar, alcohol, molasses and derivatives. The decisions considered in the modeling are taken in a weekly bases and the planning horizon is the whole sugarcane harvesting season. To solve the problems arising from modeling, the computational code was developed with the formulation coupled to optimization subroutines of Matlab. Simulations are presented by solving a case study and an illustrative example for representation of the potential of mathematical model developed. It was possible to verify the adequacy of proposed mathematical models when applied to the decisions involved in the aggregate production planning model of a milling company.