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dc.contributor.authorMazumdar, Atanu
dc.contributor.authorChugh, Tinkle
dc.contributor.authorMiettinen, Kaisa
dc.contributor.authorLópez-Ibáñez, Manuel
dc.contributor.editorDeb, Kalyanmoy
dc.contributor.editorGoodman, Erik
dc.contributor.editorCoello, Carlos A. Coello
dc.contributor.editorKlamroth, Kathrin
dc.contributor.editorMiettinen, Kaisa
dc.contributor.editorMostaghim, Sanaz
dc.contributor.editorReed, Patrick
dc.date.accessioned2019-04-09T12:15:28Z
dc.date.available2020-02-03T22:35:29Z
dc.date.issued2019
dc.identifier.citationMazumdar, A., Chugh, T., Miettinen, K., & López-Ibáñez, M. (2019). On Dealing with Uncertainties from Kriging Models in Offline Data-Driven Evolutionary Multiobjective Optimization. In K. Deb, E. Goodman, C. A. C. Coello, K. Klamroth, K. Miettinen, S. Mostaghim, & P. Reed (Eds.), <i>Evolutionary Multi-Criterion Optimization : 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019, Proceedings</i> (pp. 463-474). Springer International Publishing. Lecture Notes in Computer Science, 11411. <a href="https://doi.org/10.1007/978-3-030-12598-1_37" target="_blank">https://doi.org/10.1007/978-3-030-12598-1_37</a>
dc.identifier.otherCONVID_28954673
dc.identifier.otherTUTKAID_80865
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/63438
dc.description.abstractMany works on surrogate-assisted evolutionary multiobjective optimization have been devoted to problems where function evaluations are time-consuming (e.g., based on simulations). In many real-life optimization problems, mathematical or simulation models are not always available and, instead, we only have data from experiments, measurements or sensors. In such cases, optimization is to be performed on surrogate models built on the data available. The main challenge there is to fit an accurate surrogate model and to obtain meaningful solutions. We apply Kriging as a surrogate model and utilize corresponding uncertainty information in different ways during the optimization process. We discuss experimental results obtained on benchmark multiobjective optimization problems with different sampling techniques and numbers of objectives. The results show the effect of different ways of utilizing uncertainty information on the quality of solutions.fi
dc.format.extent757
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherSpringer International Publishing
dc.relation.ispartofEvolutionary Multi-Criterion Optimization : 10th International Conference, EMO 2019, East Lansing, MI, USA, March 10-13, 2019, Proceedings
dc.relation.ispartofseriesLecture Notes in Computer Science
dc.rightsIn Copyright
dc.subject.otherGaussian process
dc.subject.otherPareto optimality
dc.subject.otheretamodelling
dc.subject.othersurrogate
dc.titleOn Dealing with Uncertainties from Kriging Models in Offline Data-Driven Evolutionary Multiobjective Optimization
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-201903221932
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineLaskennallinen tiedefi
dc.contributor.oppiaineMultiobjective Optimization Groupfi
dc.contributor.oppiaineMathematical Information Technologyen
dc.contributor.oppiaineComputational Scienceen
dc.contributor.oppiaineMultiobjective Optimization Groupen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.date.updated2019-03-22T16:15:13Z
dc.relation.isbn978-3-030-12597-4
dc.type.coarhttp://purl.org/coar/resource_type/c_5794
dc.description.reviewstatuspeerReviewed
dc.format.pagerange463-474
dc.relation.issn0302-9743
dc.relation.numberinseries11411
dc.type.versionacceptedVersion
dc.rights.copyright© Springer Nature Switzerland AG 2019
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceInternational Conference on Evolutionary Multi-Criterion Optimization
dc.subject.ysokoneoppiminen
dc.subject.ysonormaalijakauma
dc.subject.ysomonitavoiteoptimointi
dc.subject.ysopareto-tehokkuus
dc.subject.ysomallintaminen
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p21846
jyx.subject.urihttp://www.yso.fi/onto/yso/p9478
jyx.subject.urihttp://www.yso.fi/onto/yso/p32016
jyx.subject.urihttp://www.yso.fi/onto/yso/p28039
jyx.subject.urihttp://www.yso.fi/onto/yso/p3533
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1007/978-3-030-12598-1_37
dc.type.okmA4


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