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dc.contributor.authorChu, JG
dc.contributor.authorZhang, C
dc.contributor.authorFu, GT
dc.contributor.authorLi, Y
dc.contributor.authorZhou, HC
dc.date.accessioned2016-04-27T14:03:38Z
dc.date.issued2015-08-12
dc.description.abstractThis 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 con- flicting 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.en_GB
dc.description.sponsorshipThis study was supported by the China Postdoctoral Science Foundation grants (2014M561231), and National Natural Science Foundation of China grants (51320105010, 51279021, and 51409043).en_GB
dc.identifier.citationVol. 19 (8), pp. 3557-2015en_GB
dc.identifier.doi10.5194/hess-19-3557-2015
dc.identifier.urihttp://hdl.handle.net/10871/21284
dc.language.isoenen_GB
dc.publisherEuropean Geosciences Union (EGU) / Copernicus Publicationsen_GB
dc.relation.urlhttp://hdl.handle.net/10871/18143
dc.rights© Author(s) 2015. This work is distributed under the Creative Commons Attribution 3.0 License.en_GB
dc.titleImproving multi-objective reservoir operation optimization with sensitivity-informed dimension reductionen_GB
dc.typeArticleen_GB
dc.date.available2016-04-27T14:03:38Z
dc.descriptionThis is the final version of the article. Available from European Geosciences Union via the DOI in this record.en_GB
dc.descriptionThere is another ORE record for this article: http://hdl.handle.net/10871/18143
dc.identifier.journalHydrology and Earth System Sciencesen_GB


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