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Integrated waste load allocation for river water pollution control under uncertainty: a case study of Tuojiang River, China

机译:不确定性下河水污染控制的综合废物载荷分配 - 以拓江江,中国的案例研究

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This paper presents a bi-level optimization waste load allocation programming model under a fuzzy random environment to assist integrated river pollution control. Taking account of the leader-follower decision-making in the water function zones framework, the proposed approach examines the decision making feedback relationships and conflict coordination between the river basin authority and the regional Environmental Protection Agency (EPA) based on the Stackelberg-Nash equilibrium strategy. In the pollution control system, the river basin authority, as the leader, allocates equitable emissions rights to different subareas, and the then subarea EPA, as the followers, reallocates the limited resources to various functional zones to minimize pollution costs. This research also considers the uncertainty in the water pollution management, and the uncertain input information is expressed as fuzzy random variables. The proposed methodological approach is then applied to Tuojiang River in China and the bi-level linear programming model solutions are achieved using the Karush-Kuhn-Tucker condition. Based on the waste load allocation scheme results and various scenario analyses and discussion, some operational policies are proposed to assist decision makers (DMs) cope with waste load allocation problem for integrated river pollution control for the overall benefits.
机译:本文介绍了一种模糊随机环境下的双层优化废载分配规划模型,以协助综合河流污染控制。考虑到水功能区框架中的领导者决策,拟议的方法探讨了基于Stackelberg-Nash均衡的河流域权威和区域环境保护局(EPA)之间的反馈关系和冲突协调战略。在污染控制系统中,作为领导者,作为领导者,将公平的排放权分配给不同的蛛网,当时的蛛丝EPA作为追随者将有限的资源重新分配给各种功能区,以尽量减少污染成本。该研究还考虑了水污染管理的不确定性,不确定的输入信息表示为模糊随机变量。然后将拟议的方法方法应用于中国的拓江,使用karush-kuhn-tucker条件实现了双级线性规划模型解决方案。基于废物载荷分配方案的结果和各种情景分析和讨论,提出了一些运营政策,以协助决策者(DMS)应对综合河流污染控制的废载分配问题,以实现整体效益。

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