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dc.contributor.authorDesrosiers, Jacquesen
dc.contributor.authorMladenović, Nenaden
dc.contributor.authorVilleneuve, Danielen
dc.date.accessioned2020-05-02T16:42:14Z-
dc.date.available2020-05-02T16:42:14Z-
dc.date.issued2005-01-01en
dc.identifier.issn0160-5682en
dc.description.abstractIn some schools and universities, students must sometimes be divided into several teams in such a way that each team provides a good representation of the classroom population. In this paper, two different ways of measuring the balance among teams are proposed: min-sum and min-max objective functions. For the first function and the Li-norm used in the space of attributes, an exact solution method based on a set partitioning formulation and on the enumeration of all possible team patterns is presented. For the second objective function, a set partitioning formulation is also considered, but as an approximation. In order to solve large problem instances, we have also developed metaheuristics based on variable neighbourhood search. Models and methods are tested on data from an MBA programme.en
dc.publisherTaylor & Francis-
dc.relation.ispartofJournal of the Operational Research Societyen
dc.subjectClustering | Metaheuristics | Set partitioning | Variable neighbourhood searchen
dc.titleDesign of balanced MBA student teamsen
dc.typeArticleen
dc.identifier.doi10.1057/palgrave.jors.2601775en
dc.identifier.scopus2-s2.0-12144278300en
dc.contributor.affiliationMathematical Institute of the Serbian Academy of Sciences and Arts-
dc.relation.firstpage60en
dc.relation.lastpage66en
dc.relation.issue1en
dc.relation.volume56en
dc.description.rankM22-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.grantfulltextnone-
crisitem.author.orcid0000-0001-6655-0409-
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