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dc.contributor.authorKoushki, Javad
dc.contributor.authorMiettinen, Kaisa
dc.contributor.authorSoleimani-damaneh, Majid
dc.date.accessioned2022-02-07T13:17:32Z
dc.date.available2022-02-07T13:17:32Z
dc.date.issued2022
dc.identifier.citationKoushki, J., Miettinen, K., & Soleimani-damaneh, M. (2022). LR-NIMBUS : an interactive algorithm for uncertain multiobjective optimization with lightly robust efficient solutions. <i>Journal of Global Optimization</i>, <i>83</i>(4), 843-863. <a href="https://doi.org/10.1007/s10898-021-01118-8" target="_blank">https://doi.org/10.1007/s10898-021-01118-8</a>
dc.identifier.otherCONVID_104130877
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/79666
dc.description.abstractIn this paper, we develop an interactive algorithm to support a decision maker to find a most preferred lightly robust efficient solution when solving uncertain multiobjective optimization problems. It extends the interactive NIMBUS method. The main idea underlying the designed algorithm, called LR-NIMBUS, is to ask the decision maker for a most acceptable (typical) scenario, find an efficient solution for this scenario satisfying the decision maker, and then apply the derived efficient solution to generate a lightly robust efficient solution. The preferences of the decision maker are incorporated through classifying the objective functions. A lightly robust efficient solution is generated by solving an augmented weighted achievement scalarizing function. We establish the tractability of the algorithm for important classes of objective functions and uncertainty sets. As an illustrative example, we model and solve a robust optimization problem in stock investment (portfolio selection).en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherSpringer Science and Business Media LLC
dc.relation.ispartofseriesJournal of Global Optimization
dc.rightsIn Copyright
dc.subject.otheruncertain multiple criteria optimization
dc.subject.otherrobust optimization
dc.subject.otherinteractive methods
dc.subject.otherlight robust efficiency
dc.subject.otherportfolio selection
dc.titleLR-NIMBUS : an interactive algorithm for uncertain multiobjective optimization with lightly robust efficient solutions
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202202071420
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineLaskennallinen tiedefi
dc.contributor.oppiaineMultiobjective Optimization Groupfi
dc.contributor.oppiainePäätöksen teko monitavoitteisestifi
dc.contributor.oppiaineComputational Scienceen
dc.contributor.oppiaineMultiobjective Optimization Groupen
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.pagerange843-863
dc.relation.issn0925-5001
dc.relation.numberinseries4
dc.relation.volume83
dc.type.versionacceptedVersion
dc.rights.copyright© 2022 the Authors
dc.rights.accesslevelopenAccessfi
dc.subject.ysomenetelmät
dc.subject.ysointeraktiivisuus
dc.subject.ysoportfoliot
dc.subject.ysooptimointi
dc.subject.ysoepävarmuus
dc.subject.ysomatemaattiset menetelmät
dc.subject.ysoalgoritmit
dc.subject.ysoskenaariot
dc.subject.ysoarvopaperisalkut
dc.subject.ysomonitavoiteoptimointi
dc.subject.ysopäätöksenteko
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p1913
jyx.subject.urihttp://www.yso.fi/onto/yso/p10823
jyx.subject.urihttp://www.yso.fi/onto/yso/p8330
jyx.subject.urihttp://www.yso.fi/onto/yso/p13477
jyx.subject.urihttp://www.yso.fi/onto/yso/p1722
jyx.subject.urihttp://www.yso.fi/onto/yso/p1880
jyx.subject.urihttp://www.yso.fi/onto/yso/p14524
jyx.subject.urihttp://www.yso.fi/onto/yso/p3296
jyx.subject.urihttp://www.yso.fi/onto/yso/p17562
jyx.subject.urihttp://www.yso.fi/onto/yso/p32016
jyx.subject.urihttp://www.yso.fi/onto/yso/p8743
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1007/s10898-021-01118-8
jyx.fundinginformationThis research is related to the thematic research area Decision Analytics utilizing Causal Models and Multiobjective Optimization (DEMO, jyu.fi/demo) at the University of Jyvaskyla.
dc.type.okmA1


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