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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/108878
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dc.contributor.authorNguyen, A.-
dc.contributor.authorSutton, A.-
dc.contributor.authorNeumann, F.-
dc.date.issued2015-
dc.identifier.citationTheoretical Computer Science, 2015; 561(Part A):24-36-
dc.identifier.issn0304-3975-
dc.identifier.issn1879-2294-
dc.identifier.urihttp://hdl.handle.net/2440/108878-
dc.description.abstractAbstract not available-
dc.description.statementofresponsibilityAnh Quang Nguyen, Andrew M. Sutton, Frank Neumann-
dc.language.isoen-
dc.publisherElsevier-
dc.rights© 2014 Published by Elsevier B.V.-
dc.source.urihttp://dx.doi.org/10.1016/j.tcs.2014.06.023-
dc.subjectEvolutionary multi-objective optimization; Hypervolume indicator; Genetic programming; Theory; Runtime time analysis-
dc.titlePopulation size matters: rigorous runtime results for maximizing the hypervolume indicator-
dc.typeJournal article-
dc.identifier.doi10.1016/j.tcs.2014.06.023-
pubs.publication-statusPublished-
dc.identifier.orcidNeumann, F. [0000-0002-2721-3618]-
Appears in Collections:Aurora harvest 3
Computer Science publications

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