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A Multi-Objective Best Compromise Decision Model for Real-Time Flood Mitigation Operations of Multi-Reservoir System

机译:多水库系统实时减灾运行的多目标最优折衷决策模型

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To address the decision-making problem for real-time multi-objective flood operations in multi-reservoir system, this paper develops a multi-objective best compromise decision model (MoBCDM). Utility function is used to quantitatively express the preference of decision maker, and also fuzzy analytic hierarchy process (FAHP) and segmentation and averaging (Seg/Ave) are adopted together with the preferences of decision participants (hydrologist and reservoir manager) to convert the problem into a scalar optimization. The differential evolution (DE) algorithm is implemented for obtaining the best compromise solution. The multi-objective flood operation problem in Shiguan River Basin (in China), which contains two reservoirs and three flood control points, is used as a case study. The analyses are performed to compare four historical flood operations scenarios, this model and current operating rules. The results of the analyses show that the MoBCDM outperforms all operational scenarios in terms of peak flow reduction at three flood downstream control points. In addition, the MoBCDM execution is very efficient in real-time implementation, and also weighting coefficients for the use by the MoBCDM can get high resolution calculated by FAHP.
机译:为解决多水库系统实时多目标洪水调度决策问题,建立了多目标最佳折衷决策模型(MoBCDM)。效用函数用于定量表达决策者的偏好,同时采用模糊层次分析法(FAHP)和分段平均(Seg / Ave)以及决策参与者(水文学家和水库经理)的偏好来转换问题进行标量优化。实施差分进化(DE)算法以获得最佳折衷解决方案。以中国石关河流域的多目标洪水运行问题为例,该问题包含两个水库和三个防洪点。进行分析以比较四个历史洪水作业场景,该模型和当前作业规则。分析结果表明,在三个洪水下游控制点的峰值流量减少方面,MoBCDM优于所有运行方案。此外,MoBCDM执行在实时实施中非常高效,并且MoBCDM使用的加权系数也可以通过FAHP计算得到高分辨率。

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