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An Inventory-Theory-Based Inexact Multistage Stochastic Programming Model for Water Resources Management

机译:基于库存理论的不精确多阶段随机规划模型

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摘要

An inventory-theory-based inexact multistage stochastic programming (IB-IMSP) method is developed for planning water resources systems under uncertainty. The IB-IMSP is based on inexact multistage stochastic programming and inventory theory. The IB-IMSP cannot only effectively handle system uncertainties represented as probability density functions and discrete intervals but also efficiently reflect dynamic features of system conditions under different flow levels within a multistage context. Moreover, it can provide reasonable transferring schemes (i.e., the amount and batch of transferring as well as the corresponding transferring period) associated with various flow scenarios for solving water shortage problems. The applicability of the proposed IB-IMSP is demonstrated by a case study of planning water resources management. The solutions obtained are helpful for decision makers in not only identifying different transferring schemes when the promised water is not met, but also making decisions of water allocation associated with different economic objectives.
机译:提出了一种基于清单理论的不精确多阶段随机规划(IB-IMSP)方法,用于在不确定性条件下规划水资源系统。 IB-IMSP基于不精确的多阶段随机规划和库存理论。 IB-IMSP不仅可以有效地处理以概率密度函数和离散区间表示的系统不确定性,而且可以有效地反映多级上下文中不同流量水平下系统条件的动态特征。而且,它可以提供与各种流量情况相关的合理的调水方案(即,调水的数量和批次以及相应的调水周期),以解决缺水问题。通过规划水资源管理的案例研究证明了拟议的IB-IMSP的适用性。获得的解决方案不仅有助于决策者在未达到承诺的水量时确定不同的调水方案,而且有助于做出与不同经济目标相关的水量分配决策。

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  • 来源
    《Mathematical Problems in Engineering》 |2013年第4期|482095.1-482095.15|共15页
  • 作者单位

    MOE Key Laboratory of Regional Energy Systems Optimization, Sino-Canada Energy and Environmental Research Academy, North China Electric Power University, Zhuxinzhuang, Beijing 102206, China;

    MOE Key Laboratory of Regional Energy Systems Optimization, Sino-Canada Energy and Environmental Research Academy, North China Electric Power University, Zhuxinzhuang, Beijing 102206, China;

    MOE Key Laboratory of Regional Energy Systems Optimization, Sino-Canada Energy and Environmental Research Academy, North China Electric Power University, Zhuxinzhuang, Beijing 102206, China;

    Faculty of Engineering and Applied Science, University of Regina, Regina, SK, Canada S4S 0A2;

    Faculty of Engineering and Applied Science, University of Regina, Regina, SK, Canada S4S 0A2;

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