个人信息Personal Information
教授
博士生导师
硕士生导师
任职 : 副校长、党委常委
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:建设工程学院
学科:水文学及水资源. 人工智能. 计算机应用技术. 软件工程
办公地点:综合实验4号楼 411室
联系方式:0411-84708900
电子邮箱:czhang@dlut.edu.cn
Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction
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论文类型:期刊论文
发表时间:2015-08-12
发表刊物:HYDROLOGY AND EARTH SYSTEM SCIENCES
收录刊物:SCIE、EI、Scopus
卷号:19
期号:8
页面范围:3557-3570
ISSN号:1027-5606
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.