Sugar industries are a complex inte

Sugar industries are a complex integrated system involving the growing, harvesting, transport, milling
and marketing sectors (Higgins and Muchow, 2003). This study has shown that optimized agricultural
planning promotes a homogeneous distribution of raw material along the months of crop obtaining the
maximum possible profit. An easy-to-use management tool is the best way to explore several harvesting
options to maximize profits. The use of a yield-predicting model would give better support in the
scenarios creation for optimization, mainly the maturation of sugarcane (Scarpari and Beauclair, 2004).
The transport restriction does not reproduce faithfully what happens in farming, demanding a more
complex analysis. We suggested the adoption of road-satellite systems where the best decision route and
allocation is made quickly along the day. In terms of future work, the inclusion of a model predicting
productivity will be considered, since the data used in this study was related to a crop that had already
been harvested. The goal is to get the future values and to accomplish the optimization. Without the use of
effective forecasting tools, the application of modeling software in strategic planning can result in
solutions with less realism, because “average values” do not represent what actually happens in a crop,
particularly regarding the maturation of the sugarcane (Scarpari and Beauclair, 2004).

Results (English) 1:

Sugar industries are a complex integrated system involving the growing, harvesting, transport, millingand marketing sectors (Higgins and Mucha, 2003). This study has shown that optimized agriculturalplanning promotes a homogeneous distribution of raw material along the months of crop obtaining themaximum possible profit. An easy-to-use management tool is the best way to explore several harvestingoptions to maximize profits. The use of a yield-predicting model would give better support in thescenarios creation for optimization, mainly the maturation of sugarcane (Scarpari and Beauclair, 2004).The transport restriction does not reproduce faithfully what happens in farming, demanding a morecomplex analysis. We suggested the adoption of road-satellite systems where the best decision route andallocation is made quickly along the day. In terms of future work, the inclusion of a model predictingproductivity will be considered, since the data used in this study was related to a crop that had alreadybeen harvested. The goal is to get the future values and to accomplish the optimization. Without the use ofeffective forecasting tools, the application of modeling software in strategic planning can result insolutions with less realism, because "average values" do not represent what actually happens in a crop,particularly regarding the maturation of the sugarcane (Scarpari and Beauclair, 2004).

Results (English) 3:

制糖工业是一个复杂的综合系统，涉及种植，收获，运输，加工和营销部门
（2003希金斯和马乔，）。这项研究表明，优化农业
规划促进均匀分布的原料作物获得最大可能的利润
月。一个易于使用的管理工具是探索一些收获
选择利润最大化的最佳途径。一个产量预测模型在优化
场景产生更好支持使用，主要是甘蔗（斯卡尔帕尼博克莱尔成熟和，2004）。运输限制
不会重现真实发生在农业，更复杂的分析要求
。我们建议采用路的卫星系统的最优决策路径和
配置进行快速的顺天。在今后的工作中，一个预测模型将被列入
生产率，因为在这项研究中采用的数据是一种作物已经收获相关
。我们的目标是让未来的价值和实现优化。不使用
有效的预测工具，建模软件的战略规划中应用可产生不现实
解，因为“平均值”并不代表在作物实际情况，特别是关于甘蔗
（斯卡尔帕尼博克莱尔成熟和，2004）。