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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/90636
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dc.contributor.authorBeh, E.-
dc.contributor.authorMaier, H.-
dc.contributor.authorDandy, G.-
dc.date.issued2015-
dc.identifier.citationEnvironmental Modelling and Software, 2015; 68:181-195-
dc.identifier.issn1364-8152-
dc.identifier.issn1873-6726-
dc.identifier.urihttp://hdl.handle.net/2440/90636-
dc.description.abstractAbstract not available-
dc.description.statementofresponsibilityEva H.Y. Beh, Holger R. Maier, Graeme C. Dandy-
dc.language.isoen-
dc.publisherElsevier-
dc.rights© 2015 Elsevier Ltd. All rights reserved-
dc.source.urihttp://dx.doi.org/10.1016/j.envsoft.2015.02.006-
dc.subjectOptimal sequencing/scheduling; Multi-objective optimisation; Deep uncertainty; Robustness; Scenarios; Urban water supply augmentation-
dc.titleScenario driven optimal sequencing under deep uncertainty-
dc.typeJournal article-
dc.identifier.doi10.1016/j.envsoft.2015.02.006-
pubs.publication-statusPublished-
dc.identifier.orcidMaier, H. [0000-0002-0277-6887]-
dc.identifier.orcidDandy, G. [0000-0001-5846-7365]-
Appears in Collections:Aurora harvest 7
Civil and Environmental Engineering publications

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