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dc.contributor.authorSaini, Bhupinder Singh
dc.contributor.authorEmmerich, Michael
dc.contributor.authorMazumdar, Atanu
dc.contributor.authorAfsar, Bekir
dc.contributor.authorShavazipour, Babooshka
dc.contributor.authorMiettinen, Kaisa
dc.date.accessioned2022-01-11T11:55:44Z
dc.date.available2022-01-11T11:55:44Z
dc.date.issued2022
dc.identifier.citationSaini, B. S., Emmerich, M., Mazumdar, A., Afsar, B., Shavazipour, B., & Miettinen, K. (2022). Optimistic NAUTILUS navigator for multiobjective optimization with costly function evaluations. <i>Journal of Global Optimization</i>, <i>83</i>(4), 865-889. <a href="https://doi.org/10.1007/s10898-021-01119-7" target="_blank">https://doi.org/10.1007/s10898-021-01119-7</a>
dc.identifier.otherCONVID_103601972
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/79299
dc.description.abstractWe introduce novel concepts to solve multiobjective optimization problems involving (computationally) expensive function evaluations and propose a new interactive method called O-NAUTILUS. It combines ideas of trade-off free search and navigation (where a decision maker sees changes in objective function values in real time) and extends the NAUTILUS Navigator method to surrogate-assisted optimization. Importantly, it utilizes uncertainty quantification from surrogate models like Kriging or properties like Lipschitz continuity to approximate a so-called optimistic Pareto optimal set. This enables the decision maker to search in unexplored parts of the Pareto optimal set and requires a small amount of expensive function evaluations. We share the implementation of O-NAUTILUS as open source code. Thanks to its graphical user interface, a decision maker can see in real time how the preferences provided affect the direction of the search. We demonstrate the potential and benefits of O-NAUTILUS with a problem related to the design of vehicles.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherSpringer Science and Business Media LLC
dc.relation.ispartofseriesJournal of Global Optimization
dc.rightsCC BY 4.0
dc.subject.otherinteractive methods
dc.subject.othermultiobjective optimization problems
dc.subject.otherdecision makers
dc.subject.otherpreference information
dc.subject.othercomputational cost
dc.subject.otherkriging
dc.titleOptimistic NAUTILUS navigator for multiobjective optimization with costly function evaluations
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202201111077
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineMultiobjective Optimization Groupfi
dc.contributor.oppiaineLaskennallinen tiedefi
dc.contributor.oppiaineTietojärjestelmätiedefi
dc.contributor.oppiainePäätöksen teko monitavoitteisestifi
dc.contributor.oppiaineMultiobjective Optimization Groupen
dc.contributor.oppiaineComputational Scienceen
dc.contributor.oppiaineInformation Systems Scienceen
dc.contributor.oppiaineDecision analytics utilizing causal models and multiobjective optimizationen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange865-889
dc.relation.issn0925-5001
dc.relation.numberinseries4
dc.relation.volume83
dc.type.versionpublishedVersion
dc.rights.copyright© The Author(s) 2021
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber322221
dc.relation.grantnumber311877
dc.subject.ysokriging-menetelmä
dc.subject.ysomallit (mallintaminen)
dc.subject.ysopäätöksenteko
dc.subject.ysomonitavoiteoptimointi
dc.subject.ysooptimointi
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p3126
jyx.subject.urihttp://www.yso.fi/onto/yso/p510
jyx.subject.urihttp://www.yso.fi/onto/yso/p8743
jyx.subject.urihttp://www.yso.fi/onto/yso/p32016
jyx.subject.urihttp://www.yso.fi/onto/yso/p13477
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1007/s10898-021-01119-7
dc.relation.funderResearch Council of Finlanden
dc.relation.funderResearch Council of Finlanden
dc.relation.funderSuomen Akatemiafi
dc.relation.funderSuomen Akatemiafi
jyx.fundingprogramAcademy Project, AoFen
jyx.fundingprogramResearch profiles, AoFen
jyx.fundingprogramAkatemiahanke, SAfi
jyx.fundingprogramProfilointi, SAfi
jyx.fundinginformationThis research was partly funded by the Academy of Finland (Grants 322221 and 311877). The research is related to the thematic research area Decision Analytics utilizing Causal Models and Multiobjective Optimization (DEMO), jyu.fi/demo, at the University of Jyväskylä.
dc.type.okmA1


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