A refined risk explicit interval linear programming approach for optimal watershed load reduction with objective-constraint uncertainty tradeoff analysis

作     者：Pingjian YANG Feifei DONG Yong LIU Rui ZOU Xing CHEN Huaicheng GUO 

作者机构：College of Environmental Science and Engineering Peking University the Key Laboratory of Water and Sediment Sciences Ministry of Education Beijing 100871 China School of Natural Resources and Environment University of Michigan Ann Arbor MI 48109 USA Yurman International Center for Pleantu Lakes Kunming 650034 China Tetra Tech Inc. Fairfax VA 22030 USA 

出 版 物：《Frontiers of Environmental Science & Engineering》 (环境科学与工程前沿（英文）)

年 卷 期：2016年第10卷第1期

页      面：129-140页

核心收录：

学科分类：12[管理学] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0701[理学-数学] 

基　　金：This paper was supported by the National Natural Science Foundation of China (Grant No. 41222002)  Research Fund for the Doctoral Program of Higher Education of China (20100001120020) and "China National Water Pollution Control Program" (2013ZX07102-006). Special thanks to Dr. Daniel Obenour in University of Michigan 

主　　题：refined risk explicit interval linear program-ming decision making objective-constraint uncertaintytradeoff aspiration level Lake Qionghai Watershed 

摘      要：To enhance the effectiveness of watershed load reduction decision making, the Risk Explicit Interval Linear Programming （REILP） approach was developed in previous studies to address decision risks and system returns. However, REILP lacks the capability to analyze the tradeoff between risks in the objective function and constraints. Therefore, a refined REILP model is proposed in this study to further enhance the decision support capability of the REILP approach for optimal watershed load reduction. By introducing a tradeofffactor （α） into the total risk function, the refined REILP can lead to different compromises between risks associated with the objective functions and the constraints. The proposed model was illustrated using a case study that deals with uncertainty- based optimal load reduction decision making for Lake Qionghai Watershed, China. A risk tradeoff curve with different values of a was presented to decision makers as a more flexible platform to support decision formulation. The results of the standard and refined REILP model were compared under 11 aspiration levels. The results demon- strate that, by applying the refined REILP, it is possible to obtain solutions that preserve the same constraint risk as that in the standard REILP but with lower objective risk, which can provide more effective guidance for decision makers.