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Uncertainty-Based Multi-Objective Decision Making with Hierarchical Reliability Analysis Under Water Resources and Environmental Constraints
- 作者:Feifei Dong ; Yong Liu ; Han Su ; Zhongyao Liang ; Rui Zou…
- 关键词:Water resources allocation ; Stochastic programming ; Tradeoff analysis ; Multi ; criteria decision analysis ; Multi ; objective evolutionary algorithm ; Optimization
- 刊名:Water Resources Management
- 出版年:2016
- 出版时间:January 2016
- 年:2016
- 卷:30
- 期:2
- 页码:805-822
- 全文大小:988 KB
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- 作者单位:Feifei Dong (1)
Yong Liu (1) Han Su (1) Zhongyao Liang (1) Rui Zou (2) (3) Huaicheng Guo (1)
1. College of Environmental Science and Engineering, Key Laboratory of Water and Sediment Sciences (MOE), Peking University, Beijing, 100871, China 2. Tetra Tech, Inc, 10306 Eaton Place, Ste 340, Fairfax, VA, 22030, USA 3. Yunnan Key Laboratory of Pollution Process and Management of Plateau Lake-Watershed, Kunming, 650034, China
- 刊物类别:Earth and Environmental Science
- 刊物主题:Earth sciences
Hydrogeology Geotechnical Engineering Meteorology and Climatology Civil Engineering Environment
- 出版者:Springer Netherlands
- ISSN:1573-1650
文摘
Rapid urbanization and population growth have resulted in worldwide serious water shortage and environmental deterioration. It is then essential for efficient and feasible allocation of scarce water and environment resources to the competing users. Due to inherent uncertainties, decision making for resources allocation is vulnerable to failure. The scheme feasibility can be evaluated by reliability, representing the failure probability. A progressive reliability-oriented multi-objective (PROMO) optimal decision-making procedure is proposed in this study to deal with problems with numerous reliability objectives. Dimensionality of the objectives is reduced by a top-down hierarchical reliability analysis (HRA) process combining optimization with evaluation. Pareto solutions of the reformulated model, representing alternative schemes non-dominated with each other, are generated by a metalmodel-based optimization algorithm. Evaluation and identification of Pareto solutions are conducted by multi-criteria decision analysis (MCDA). The PROMO procedure is demonstrated for a case study on industrial structure transformation under strict constraints of water resources and total environmental emissions amounts in Guangzhou City, South China. The Pareto front reveals tradeoffs between economic returns of the industries and system reliability. For different reliability preference scenarios, the Pareto solutions are ranked and the top-rated one was recommended for implementation. The model results indicate that the PROMO procedure is effective for model solving and scheme selection of uncertainty-based multi-objective decision making. Keywords Water resources allocation Stochastic programming Tradeoff analysis Multi-criteria decision analysis Multi-objective evolutionary algorithm Optimization
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