DOI: 10.5194/hess-19-3557-2015
Scopus记录号: 2-s2.0-84939132876
论文题名: Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction
作者: Chu J ; , Zhang C ; , Fu G ; , Li Y ; , Zhou H
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2015
卷: 19, 期: 8 起始页码: 3557
结束页码: 3570
语种: 英语
Scopus关键词: Decision making
; Economic and social effects
; Optimization
; Problem solving
; Sensitivity analysis
; Computational demands
; Global sensitivity analysis
; Multi-objective evolutionary optimizations
; Multi-reservoir systems
; Optimization problems
; Reservoir operation optimizations
; Reservoir performance
; Trade-off relationship
; Multiobjective optimization
; computer simulation
; efficiency measurement
; genetic algorithm
; multiobjective programming
; optimization
; performance assessment
; reservoir
; reservoir impoundment
; sensitivity analysis
; trade-off
; China
; Dahuofang Reservoir
; Liaoning
英文摘要: This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed method dramatically reduces the computational demands required for attaining high-quality approximations of optimal trade-off relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed dimension reduction and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform dimension reduction of optimization problems when solving complex multi-objective reservoir operation problems. © Author(s) 2015. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78445
Appears in Collections: 气候变化事实与影响
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作者单位: School of Hydraulic Engineering, Dalian University of Technology, Dalian, China; Centre for Water Systems, College of Engineering, Mathematics and Physical Sciences, University of Exeter, North Park Road, Harrison Building, Exeter, United Kingdom
Recommended Citation:
Chu J,, Zhang C,, Fu G,et al. Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction[J]. Hydrology and Earth System Sciences,2015-01-01,19(8)