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dc.contributor.authorZhou-Kangas, Yue
dc.contributor.authorMiettinen, Kaisa
dc.contributor.authorSindhya, Karthik
dc.contributor.editorBaum, Marcus
dc.contributor.editorBrenner, Gunther
dc.contributor.editorGrabowski, Jens
dc.contributor.editorHanschke, Thomas
dc.contributor.editorHartmann, Stefan
dc.contributor.editorSchöbel, Anita
dc.date.accessioned2018-08-22T12:12:38Z
dc.date.available2018-08-22T12:12:38Z
dc.date.issued2018
dc.identifier.citationZhou-Kangas, Y., Miettinen, K., & Sindhya, K. (2018). Interactive Multiobjective Robust Optimization with NIMBUS. In M. Baum, G. Brenner, J. Grabowski, T. Hanschke, S. Hartmann, & A. Schöbel (Eds.), <i>Simulation Science : First International Workshop, SimScience 2017, Göttingen, Germany, April 27–28, 2017, Revised Selected Papers</i> (pp. 60-76). Springer. Communications in Computer and Information Science, 889. <a href="https://doi.org/10.1007/978-3-319-96271-9_4" target="_blank">https://doi.org/10.1007/978-3-319-96271-9_4</a>
dc.identifier.otherCONVID_28203235
dc.identifier.otherTUTKAID_78482
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/59313
dc.description.abstractIn this paper, we introduce the MuRO-NIMBUS method for solving multiobjective optimization problems with uncertain parameters. The concept of set-based minmax robust Pareto optimality is utilized to tackle the uncertainty in the problems. We separate the solution process into two stages: the pre-decision making stage and the decision making stage. We consider the decision maker’s preferences in the nominal case, i.e., with the most typical or undisturbed values of the uncertain parameters. At the same time, the decision maker is informed about the objective function values in the worst case to support her/him to make an informed decision. To help the decision maker to understand the behaviors of the solutions, we visually present the objective function values. As a result, the decision maker can find a preferred balance between robustness and objective function values under the nominal case.fi
dc.format.extent273
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofSimulation Science : First International Workshop, SimScience 2017, Göttingen, Germany, April 27–28, 2017, Revised Selected Papers
dc.relation.ispartofseriesCommunications in Computer and Information Science
dc.rightsIn Copyright
dc.subject.othermultiple criteria decision making
dc.subject.otherrobustness
dc.subject.otherinteractive methods
dc.subject.otherrobust Pareto optimality
dc.titleInteractive Multiobjective Robust Optimization with NIMBUS
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-201808213893
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.date.updated2018-08-21T12:15:13Z
dc.relation.isbn978-3-319-96270-2
dc.description.reviewstatuspeerReviewed
dc.format.pagerange60-76
dc.relation.issn1865-0929
dc.relation.numberinseries889
dc.type.versionacceptedVersion
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceSimulation Science
dc.subject.ysomonitavoiteoptimointi
dc.subject.ysopäätöksenteko
dc.subject.ysoepävarmuus
dc.subject.ysopareto-tehokkuus
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p32016
jyx.subject.urihttp://www.yso.fi/onto/yso/p8743
jyx.subject.urihttp://www.yso.fi/onto/yso/p1722
jyx.subject.urihttp://www.yso.fi/onto/yso/p28039
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1007/978-3-319-96271-9_4


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