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Robust optimization model for water quality management in river systems

机译:河流系统水质管理鲁棒优化模型

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An advanced robust optimization (RO) model to manage water quality in river systems is proposed which embraces every conceivable uncertainty present in water quality problems and is applicable to a network of streams, as an improvement over our earlier RO model. Biochemical oxygen demand (BOD) and dissolved oxygen (DO) concentrations of the incoming water from the upstream ends are added in a family of basic uncertainty parameters. In order to widen a spectrum of feasible solutions, the number of constraints associated with in-stream water quality standards is reduced. An optimization problem of BOD loading to a river system is solved with consideration to the solution robustness related to variability of the BOD load and to the model robustness related to violations of the in-stream water quality standards prescribed. Through an optimization example, it is demonstrated that the model proposed successfully provides a series of alternative strategies for water quality management in a multitudinously delimited network of streams.
机译:提出了一种先进的鲁棒优化(RO)模型,用于管理河流系统中的水质,其包括水质问题中存在的每一个可想到的不确定性,并且适用于流网络,作为我们早期的RO模型的改进。在基本不确定性参数的家族中加入生物化学需氧量(BOD)和溶解的氧(DO)从上游末端的进入水的浓度。为了扩大可行解决方案的频谱,减少了与流水质标准相关的限制的数量。解决了与河流系统的博客加载到河流系统的优化问题,以考虑到与BOD负载的可变性以及与违反规定的流式水质标准相关的模型稳健性的溶液稳健性。通过优化示例,证明该模型成功提供了一系列替代策略,用于在多重分隔的流网络中提供水质管理。

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