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Application of Fuzzy Multi-Objective Programming in Optimization of Crop Production Planning

机译:模糊多目标规划在作物生产计划优化中的应用

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Planning for the optimal use of productive resources in agricultural systems leads to the conservation in addition to the promotion of farmers' socio-economical conditions. Being certain or precise in any decision making in agricultural planning is impossible. Fuzzy mathematical programming techniques, developed in recent decades, are the most appropriate and applicable approaches to include the uncertainty in crop planning and productive resources management. Using the multi-objective Fuzzy Goal Programming (FGP) approach, the farming system of a rural region located in the central of Iran has investigated in this study in order to identify the optimal cropping pattern and land use planning under uncertainty. For this purpose, several objectives like maximizing the area under cultivation, net return and employment opportunities and simultaneously the land, capital, monthly water and labor force requirements and availabilities, crop rotation and a crop lower bound production constraint impreciselyconsidered as fuzzy goals. The needed data gathered through fieldwork operations. In multi-objective programming context, as the results revealed, the constraints of the productive resources are more determinant in land allocation than the objective functions. To illustrate the precedence of the cited FGP model, the results were quantitatively compared with the existing situation and a crisp goal programming model containing the same objectives and constraints. The precedence mainly pertained to the goals of objective functions. The crop-mix in FGP pattern change achieved considerable conservation of water and capital resources and improvement of income generation of the agricultural system, with almost no variation in the cultivation area.
机译:对农业系统中生产资源的最佳利用进行规划,不仅可以促进农民的社会经济条件,还可以起到保护作用。在农业计划的任何决策中都不能确定或精确。近几十年来发展起来的模糊数学编程技术是最合适和适用的方法,可以将作物计划和生产资源管理中的不确定性包括在内。使用多目标模糊目标规划(FGP)方法,本研究对位于伊朗中部的农村地区的耕作制度进行了调查,以便确定不确定性下的最佳耕作模式和土地利用规划。为此,不精确地将模糊增长的目标视为几个目标,例如最大化耕种面积,净回报和就业机会,同时土地,资本,每月水和劳动力的需求和可用性,作物轮作和作物下限生产约束。通过野外作业收集所需的数据。结果表明,在多目标规划的背景下,土地资源分配中的生产资源约束比目标函数更重要。为了说明引用的FGP模型的优越性,将结果与现有情况和包含相同目标和约束的清晰目标编程模型进行了定量比较。优先顺序主要与目标功能的目标有关。 FGP模式改变中的农作物混合实现了相当大的水和资本资源节约,并改善了农业系统的创收能力,耕地面积几乎没有变化。

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