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dc.contributor.authorHartikainen, Markus
dc.contributor.authorMiettinen, Kaisa
dc.contributor.authorWiecek, Margaret M.
dc.date.accessioned2016-07-29T09:38:18Z
dc.date.available2016-07-29T09:38:18Z
dc.date.issued2012
dc.identifier.citationHartikainen, M., Miettinen, K., & Wiecek, M. M. (2012). PAINT: Pareto front interpolation for nonlinear multiobjective optimization. <i>Computational Optimization and Applications</i>, <i>52</i>(3), 845-867. <a href="https://doi.org/10.1007/s10589-011-9441-z" target="_blank">https://doi.org/10.1007/s10589-011-9441-z</a>
dc.identifier.otherCONVID_21564912
dc.identifier.otherTUTKAID_51633
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/50901
dc.description.abstractA method called PAINT is introduced for computationally expensive multiobjective optimization problems. The method interpolates between a given set of Pareto optimal outcomes. The interpolation provided by the PAINT method implies a mixed integer linear surrogate problem for the original problem which can be optimized with any interactive method to make decisions concerning the original problem. When the scalarizations of the interactive method used do not introduce nonlinearity to the problem (which is true e.g., for the synchronous NIMBUS method), the scalarizations of the surrogate problem can be optimized with available mixed integer linear solvers. Thus, the use of the interactive method is fast with the surrogate problem even though the problem is computationally expensive. Numerical examples of applying the PAINT method for interpolation are included.
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofseriesComputational Optimization and Applications
dc.relation.urihttp://www.springerlink.com/content/x8548782129x3832/?MUD=MP
dc.subject.otherPareto-optimaalisuus
dc.subject.otherapproksimaatio
dc.subject.otherMultiobjective optimization
dc.subject.otherPareto optimality
dc.titlePAINT: Pareto front interpolation for nonlinear multiobjective optimization
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201607283684
dc.contributor.laitosTietotekniikan laitosfi
dc.contributor.laitosDepartment of Mathematical Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.date.updated2016-07-28T12:15:03Z
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange845-867
dc.relation.issn0926-6003
dc.relation.numberinseries3
dc.relation.volume52
dc.type.versionacceptedVersion
dc.rights.copyright© Springer International Publishing AG
dc.rights.accesslevelopenAccessfi
dc.subject.ysomonitavoiteoptimointi
dc.subject.ysoapproksimointi
jyx.subject.urihttp://www.yso.fi/onto/yso/p32016
jyx.subject.urihttp://www.yso.fi/onto/yso/p4982
dc.relation.doi10.1007/s10589-011-9441-z
dc.type.okmA1


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