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dc.contributor.authorDächert, Kerstin*
dc.contributor.authorKlamroth, Kathrin*
dc.contributor.authorLacour, Renaud*
dc.contributor.authorVanderpooten, Daniel*
dc.date.accessioned2017-02-15T17:08:55Z
dc.date.available2017-02-15T17:08:55Z
dc.date.issued2017
dc.identifier.issn0377-2217
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/16255
dc.language.isoenen
dc.subjectMulti-objective optimization
dc.subjectNondominated set
dc.subjectSearch region
dc.subjectLocal upper bounds
dc.subjectScalarization
dc.subject.ddc003en
dc.titleEfficient computation of the search region in multi-objective optimization
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenMulti-objective optimization procedures usually proceed by iteratively producing new solutions. For this purpose, a key issue is to determine and efficiently update the search region, which corresponds to the part of the objective space where new nondominated points could lie. In this paper we elaborate a specific neighborhood structure among local upper bounds. Thanks to this structure, the update of the search region with respect to a new point can be performed more efficiently compared to existing approaches. Moreover, the neighborhood structure provides new insight into the search region and the location of nondominated points.
dc.relation.isversionofjnlnameEuropean Journal of Operational Research
dc.relation.isversionofjnlvol260
dc.relation.isversionofjnlissue3
dc.relation.isversionofjnldate2017
dc.relation.isversionofjnlpages841-855
dc.relation.isversionofdoi10.1016/j.ejor.2016.05.029
dc.subject.ddclabelRecherche opérationnelleen
dc.description.ssrncandidatenon
dc.description.halcandidateoui
dc.description.readershiprecherche
dc.description.audienceInternational
dc.relation.Isversionofjnlpeerreviewedoui
dc.date.updated2017-03-22T14:23:51Z
hal.person.labIds115536*
hal.person.labIds115536*
hal.person.labIds115536*
hal.person.labIds989*
hal.identifierhal-01505660*
hal.faultCode{"duplicate-entry":{"hal-01505660":{"doi":"1.0"}}}


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