Resolution of the Min-Max Optimization Problem Applied in the Agricultural Sector with the Estimation of Yields by Nonparametric Statistical Approaches

Q3 Mathematics Abstract and Applied Analysis Pub Date : 2021-04-14 DOI:10.1155/2021/6691678
Ghizlane Kouaiba, D. Mentagui
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Abstract

The ultimate objective of the problem under study is to apply the min-max tool, thus making it possible to optimize the default risks linked to several areas: the agricultural sector, for example, which requires the optimization of the default risk using the following elements: silage crops, annual consumption requirements, and crops produced for a given year. To minimize the default risk in the future, we start, in the first step, by forecasting the total budget of agriculture investment for the next 20 years, then distribute this budget efficiently between the irrigation and construction of silos. To do this, Bangladesh was chosen as an empirical case study given the availability of its data on the FAO website; it is considered a large agricultural country in South Asia. In this article, we give a detailed and original in-depth study of the agricultural planning model through a calculating algorithm suggested to be coded on the R software thereafter. Our approach is based on an original statistical modeling using nonparametric statistics and considering an example of a simulation involving agricultural data from the country of Bangladesh. We also consider a new pollution model, which leads to a vector optimization problem. Graphs illustrate our quantitative analysis.
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用非参数统计方法求解农业部门产量估计中的最小-最大优化问题
所研究问题的最终目标是应用最小-最大工具,从而有可能优化与几个领域相关的违约风险:例如,农业部门需要使用以下要素优化违约风险:青贮作物、年消费需求和给定年份的作物产量。为了减少未来的违约风险,我们首先预测未来20年农业投资的总预算,然后将预算有效地分配到灌溉和建造筒仓之间。为此,考虑到粮农组织网站上提供的数据,选择孟加拉国作为实证案例研究;它被认为是南亚的农业大国。在本文中,我们通过一个建议在R软件上编码的计算算法,对农业规划模型进行了详细而新颖的深入研究。我们的方法基于使用非参数统计的原始统计建模,并考虑了一个涉及孟加拉国农业数据的模拟示例。我们还考虑了一个新的污染模型,它会导致向量优化问题。图表说明了我们的定量分析。
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来源期刊
CiteScore
2.30
自引率
0.00%
发文量
36
审稿时长
3.5 months
期刊介绍: Abstract and Applied Analysis is a mathematical journal devoted exclusively to the publication of high-quality research papers in the fields of abstract and applied analysis. Emphasis is placed on important developments in classical analysis, linear and nonlinear functional analysis, ordinary and partial differential equations, optimization theory, and control theory. Abstract and Applied Analysis supports the publication of original material involving the complete solution of significant problems in the above disciplines. Abstract and Applied Analysis also encourages the publication of timely and thorough survey articles on current trends in the theory and applications of analysis.
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