Robust optimization evaluation of reliance on locally produced foods
Robust optimization evaluation of reliance on locally produced foods
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对本地生产食品的依赖度的稳健优化评估
DOI：
10.1007/s10669-016-9617-2
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发表时间：
2017
影响因子：
--
通讯作者：
McGarvey, Ronald G.
中科院分区：
文献类型：
--
作者：
Dundar, Bayram;Costello, Christine;McGarvey, Ronald G.
虽然当地粮食生产在发展当地经济和减少运输产生的温室气体方面可能是有益的，但由于产量的变异性，侧重于当地粮食生产的可持续发展战略可能会产生自身的风险。我们开发了一个稳健的优化(RO)模型，以确定种植满足当地人口(考虑性别和年龄)卡路里和营养需求的粮食所需的最低土地数量(农田和牧场)。该模型已应用于人口约17万的密苏里州布恩县。布恩县面积1790平方公里，其中16%的土地被定义为农田，30%的土地被定义为牧场。该模型包括来自17种可能生产的食物的27种营养素：6种水果和蔬菜，5种谷物和6种动物性食品。产量估计是基于美国主要的农业方法。我们首先运行我们的模型，假设没有变化，使用中间价收益率估计。然后，为了量化不同粮食类型产量的不确定性，我们使用10年来的历史产量数据来估计这种变异性，并在这些变异性估计下运行我们的RO模型。我们比较了两个模型的结果，以说明数据不确定性对满足社区可持续当地粮食的影响。解决方案表明，在确定的土地面积内，布恩县人口的营养需求可以得到满足。
While local food production may be beneficial in terms of developing the local economy and reducing greenhouse gases from transportation, sustainability strategies focused on local food production may generate their own risks due to yield variability. We have developed a robust optimization (RO) model to determine the minimum amount of land (cropland and pasture) required to grow food items that would satisfy a local population’s (accounting for gender and age) calorie and nutrient needs. This model has been applied to Boone County, Missouri, which has a population of approximately 170,000. Boone County is 1790 km2, with 16% of the land defined as cropland and 30% defined as pasture. The model includes 27 nutrients from 17 potential foods that could be produced: six fruits and vegetables, five grains and six animal-sourced foods. Yield estimates are based on the predominate methods of agriculture in the USA. We first run our model assuming no variability, using the midpoint yield estimates. Then, to quantify uncertainty in yield for different food types, we use historical yield data over 10 years to estimate this variability and run our RO model under these variability estimates. We compare the two model results to illustrate the impact of data uncertainty on meeting sustainable local food for communities. Solutions suggest that nutrition needs can be met for the Boone County population within the land area defined.
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影响因子：
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