Modelo matemático para determinação do custo e produção de energia na cultura da cana-de-açúcar

• Autor(a) principal: Ramos, Rômulo Pimentel [UNESP]
• Data de Publicação: 2012
• Outros Autores: Silva, Helenice de Oliveira Florentino [UNESP]
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.17224/EnergAgric.2012v27n1p122-137; http://hdl.handle.net/11449/137152
• topic: Sugarcane; Optimization; Cost minimization; Cana-de-açúcar; Otimização; Minimização de custo

Sugarcane has a great social and economic importance for Brazil. Brazil is the largest producer of sugarcane in the world. In 2009/10 crop production was 597.8 million tons, up 4.4% compared to 571.40 million tons harvested in 2008 /09. On the other hand, the accelerated growth of this sector has brought about a number of larger problems from structural and environmental orders making the management of companies more difficult. Thus it is important to know the entire process of producing sugarcane from soil preparation to industrialization that being the reception of the sugarcane until its output as a finished product to seek ways to minimize production cost. This is proving the need of developing tools that will assist managers in corporate decision making. The mathematical modeling can be utilized with an important source of production estimates for this sector, facilitating calculations and aiding in decisions. The objective of this work was to study the entire production chain of sugarcane and investigate mathematical models to estimate quantitatively the energy balance and production cost of the production phase of sugarcane. We developed a mathematical model and spreadsheet to estimate the cost of the sugarcane production process to determine which area in hectares that each variety of cane should be planted in order to obtain the lowest possible cost in the production process. For the area using manual harvesting the model was determined using three varieties: SP80-1816, SP80-3280 and RB855113, also the area of mechanical harvesting has been determined by using four varieties: SP80-1816, SP80-3280, RB855536 and SP70-1143. The linear programming model proposed to minimize costs along with a spreadsheet that has been implemented in this work shows promising tools to assist with the management of companies in the industry.