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A robust interval-based minimax-regret analysis approach for the identification of optimal water-resources-allocation strategies under uncertainty

机译:基于不确定区间的鲁棒最小极大值后悔分析方法,用于确定不确定性下的最优水资源分配策略

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In this study, a robust interval-based minimax-regret analysis (RIMA) method is developed and applied to the identification of optimal water-resources-allocation strategies under uncertainty. The developed RIMA approach can address uncertainties with multiple presentations. Moreover. it can be used for analyzing all possible scenarios associated with different system costs/benefits and risk levels without making assumptions on probabilistic distributions for random variables. In its solution process, an interval-element cost/benefit matrix can be transformed into an interval-element regret matrix, such that the decision makers can identify desired strategies based on inexact minimax regret (IMMR) criterion. Moreover, the fuzzy decision space is delimited into a more robust one through dimensional enlargement of the original fuzzy constraints. The developed method is applied to a case study of planning water resources allocation under uncertainty. The results indicate that reasonable solutions have been generated. They can help decision makers identify desired strategies for water-resources allocation with a compromise between maximized system benefit and minimized system-failure risk.
机译:在这项研究中,鲁棒的基于间隔的最小极大值后悔分析(RIMA)方法被开发并应用于不确定性条件下最优水资源分配策略的识别。先进的RIMA方法可以通过多次演示来解决不确定性问题。此外。它可以用于分析与不同系统成本/收益和风险水平相关的所有可能情况,而无需假设随机变量的概率分布。在其求解过程中,可以将间隔元素成本/收益矩阵转换为间隔元素后悔矩阵,以便决策者可以基于不精确的最小最大后悔(IMMR)准则确定所需的策略。而且,通过原始模糊约束的尺寸扩大,将模糊决策空间定界为更鲁棒的一个。将该方法应用于不确定情况下规划水资源分配的案例研究。结果表明已经产生了合理的解决方案。它们可以帮助决策者在最大的系统收益和最小的系统故障风险之间做出折衷,从而确定水资源分配的理想策略。

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