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Dependent-Chance Goal Programming for Water Resources Management under Uncertainty

机译:不确定性下水资源管理的依赖机会目标规划

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摘要

Without sufficient data, consulting experts is a good way to quantify unknown parameters in water resources management which will result in human uncertainty. The aim of this paper is to introduce a new tool-uncertainty theory to deal with such uncertainty which is treated as uncertain variable with uncertainty distribution. And a dependent-chance goal programming (DCGP) model is provided for water resources management under such circumstance. In the model uncertain measure is used to measure possibility that an event will occur which is maximized by minimizing the deviation (positive or negative deviation) from target of objective event under a given priority structure. In the end, the developed model is applied to a numerical example to illustrate the effectiveness of the model. The result obtained contributes to the desired water-allocation schemes for decision-markers.
机译:没有足够的数据,咨询专家是量化水资源管理中未知参数的好方法,这将导致人类不确定性。本文的目的是引入新的工具 - 不确定性理论,以处理这种不确定性,其被视为不确定的变量,不确定分布。在这种情况下提供了依赖机构的目标编程(DCGP)模型,用于水资源管理。在模型不确定的测量中用于测量发生事件的可能性,这将通过最小化来自给定优先级结构下的客观事件的目标的偏差(正或负偏差)来最大化。最后,开发模型应用于数值示例以说明模型的有效性。所得到的结果有助于决策标记的所需水分配方案。

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