Robust Targeting of Resource Requirement in a Continuous Water Network
Robust Targeting of Resource Requirement in a Continuous Water Network
复制标题
连续供水网络中资源需求的稳健目标
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
N. Chaturvedi
中科院分区：
文献类型：
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作者：
P. Kumawat;N. Chaturvedi
本文提出了一个稳健的公式来计算工业中连续过程的淡水需求目标。所提出的鲁棒对应线性规划公式包括资源最小化约束，并已被应用于优化外部资源，以满足未满足的需求，在源汇水分配问题，确定性流量和确定性质量。与传统的基于情景的随机规划方法相比，鲁棒对应优化方法具有独特的优势。相应的优化问题的规模不随不确定参数的数量呈指数增长。鲁棒优化适用性已被应用到具有不确定质量和流量的资源管理网络中，用于应用具有所需可靠性的单个源和需求。所得到的公式保持了数学模型的线性，并且可以控制每个约束的保守性程度，并保证问题的可行性。决策者还可以在不确定性水平和约束违反的上限概率之间进行权衡。该模型将帮助规划者在不确定条件下确定需水量，并相应地做好必要的准备，使过程不受不确定性的影响，以满足需求。
In this paper, a robust formulation is proposed to calculate the target of freshwater requirement as a resource for continuous processes in industries. The proposed robust counterpart linear programming formulation includes resource minimization constraints and has been applied to optimize the external resource, to satisfy unmet demands in source-sink water allocation problems, with deterministic flows and deterministic quality. Compared to the traditional-scenario-based stochastic programming method, a robust counterpart optimization method has a unique advantage. The scale of the corresponding optimization problem does not increase exponentially with the number of uncertain parameters. Robust optimization applicability has been applied to resource management networks with uncertain qualities and flows for the application of individual sources and demands with the desired reliability. The resultant formulation preserves the linearity of the mathematical model and can control the degree of conservatism for every constraint and guarantees feasibility for the problem. Decision-makers can also make a trade-off between uncertainty level and an upper probability of constraint violation. This model will assist the planner to decide the water requirement under uncertain conditions and to do the necessary preparation accordingly and immunes the process against uncertainties to satisfy demands.