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dc.contributor.authorMaier, H.R.
dc.contributor.authorKapelan, Zoran
dc.contributor.authorKasprzyk, J.
dc.contributor.authorKollat, J.
dc.contributor.authorMatott, L.S.
dc.contributor.authorCunha, M.C.
dc.contributor.authorDandy, G.C.
dc.contributor.authorGibbs, M.S.
dc.contributor.authorKeedwell, Edward
dc.contributor.authorMarchi, A.
dc.contributor.authorOstfeld, A.
dc.contributor.authorSavic, Dragan
dc.contributor.authorSolomatine, D.P.
dc.contributor.authorVrugt, J.A.
dc.contributor.authorZecchin, A.C.
dc.contributor.authorMinsker, B.S.
dc.contributor.authorBarbour, E.J.
dc.contributor.authorKuczera, G.
dc.contributor.authorPasha, F.
dc.contributor.authorCastelletti, A.
dc.contributor.authorGiuliani, M.
dc.contributor.authorReed, P.M.
dc.date.accessioned2015-04-01T15:20:31Z
dc.date.issued2014
dc.description.abstractThe development and application of evolutionary algorithms (EAs) and other metaheuristics for the optimisation of water resources systems has been an active research field for over two decades. Research to date has emphasized algorithmic improvements and individual applications in specific areas (e.g. model calibration, water distribution systems, groundwater management, river-basin planning and management, etc.). However, there has been limited synthesis between shared problem traits, common EA challenges, and needed advances across major applications. This paper clarifies the current status and future research directions for better solving key water resources problems using EAs. Advances in understanding fitness landscape properties and their effects on algorithm performance are critical. Future EA-based applications to real-world problems require a fundamental shift of focus towards improving problem formulations, understanding general theoretic frameworks for problem decompositions, major advances in EA computational efficiency, and most importantly aiding real decision-making in complex, uncertain application contexts.en_GB
dc.identifier.citationVol. 62, pp. 271 - 299en_GB
dc.identifier.doi10.1016/j.envsoft.2014.09.013
dc.identifier.urihttp://hdl.handle.net/10871/16653
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.relation.urlhttp://dx.doi.org/10.1016/j.envsoft.2014.09.013en_GB
dc.subjectOptimisationen_GB
dc.subjectWater resourcesen_GB
dc.subjectEvolutionary algorithmsen_GB
dc.subjectMetaheuristicsen_GB
dc.subjectReviewen_GB
dc.subjectResearch directionsen_GB
dc.titleEvolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directionsen_GB
dc.typeArticleen_GB
dc.date.available2015-04-01T15:20:31Z
dc.identifier.issn1364-8152
dc.descriptionCopyright © 2014 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Environmental Modelling and Software. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Environmental Modelling and Software Vol. 62 (2014), DOI: 10.1016/j.envsoft.2014.09.013en_GB
dc.identifier.eissn1873-6726
dc.identifier.journalEnvironmental Modelling and Softwareen_GB


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