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dc.contributor.authorZhou-Kangas, Yue
dc.contributor.authorMiettinen, Kaisa
dc.contributor.editorAuger, Anne
dc.contributor.editorFonseca, Carlos M.
dc.contributor.editorLourenço, Nuno
dc.contributor.editorMachado, Penousal
dc.contributor.editorPaquete, Luís
dc.contributor.editorWhitley, Darrell
dc.date.accessioned2018-09-27T10:30:00Z
dc.date.available2019-08-25T21:35:35Z
dc.date.issued2018
dc.identifier.citationZhou-Kangas, Y., & Miettinen, K. (2018). A Simple Indicator Based Evolutionary Algorithm for Set-Based Minmax Robustness. In A. Auger, C. M. Fonseca, N. Lourenço, P. Machado, L. Paquete, & D. Whitley (Eds.), <i>Parallel Problem Solving from Nature - PPSN XV : 15th International Conference, Coimbra, Portugal, September 8–12, 2018, Proceedings, Part 1</i> (pp. 287-297). Springer. Lecture Notes in Computer Science, 11101. <a href="https://doi.org/10.1007/978-3-319-99253-2_23" target="_blank">https://doi.org/10.1007/978-3-319-99253-2_23</a>
dc.identifier.otherCONVID_28273787
dc.identifier.otherTUTKAID_78901
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/59706
dc.description.abstractFor multiobjective optimization problems with uncertain parameters in the objective functions, different variants of minmax robustness concepts have been defined in the literature. The idea of minmax robustness is to optimize in the worst case such that the solutions have the best objective function values even when the worst case happens. However, the computation of the minmax robust Pareto optimal solutions remains challenging. This paper proposes a simple indicator based evolutionary algorithm for robustness (SIBEA-R) to address this challenge by computing a set of non-dominated set-based minmax robust solutions. In SIBEA-R, we consider the set of objective function values in the worst case of each solution. We propose a set-based non-dominated sorting to compare the objective function values using the definition of lower set less order for set-based dominance. We illustrate the usage of SIBEA-R with two example problems. In addition, utilization of the computed set of solutions with SIBEA-R for decision making is also demonstrated. The SIBEA-R method shows significant promise for finding non-dominated set-based minmax robust solutions.fi
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofParallel Problem Solving from Nature - PPSN XV : 15th International Conference, Coimbra, Portugal, September 8–12, 2018, Proceedings, Part 1
dc.relation.ispartofseriesLecture Notes in Computer Science
dc.rightsIn Copyright
dc.subject.otherminmax robust
dc.subject.otherPareto optimal solutions
dc.subject.otherhypervolume
dc.subject.otherset-based dominance
dc.subject.otherSIBEA uncertainty
dc.titleA Simple Indicator Based Evolutionary Algorithm for Set-Based Minmax Robustness
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-201809204195
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.updated2018-09-20T12:15:14Z
dc.relation.isbn978-3-319-99252-5
dc.description.reviewstatuspeerReviewed
dc.format.pagerange287-297
dc.relation.issn0302-9743
dc.relation.numberinseries11101
dc.type.versionacceptedVersion
dc.rights.copyright© Springer Nature 2018
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceInternational Conference on Parallel Problem Solving From Nature
dc.subject.ysomonitavoiteoptimointi
dc.subject.ysopareto-tehokkuus
dc.subject.ysoalgoritmit
dc.format.contentfulltext
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/p14524
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1007/978-3-319-99253-2_23


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