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The mean-partition problem

dc.citation.epage31en_US
dc.citation.issue1en_US
dc.citation.spage21en_US
dc.citation.volume36en_US
dc.citation.woscount1
dc.contributor.authorChang, Fei-Hwangen_US
dc.contributor.authorHwang, Frank K.en_US
dc.contributor.authorRothblum, Uriel G.en_US
dc.contributor.department應用數學系zh_TW
dc.contributor.departmentDepartment of Applied Mathematicsen_US
dc.date.accessioned2014-12-08T15:16:00Z
dc.date.available2014-12-08T15:16:00Z
dc.date.issued2006-09-01en_US
dc.description.abstractIn mean-partition problems the goal is to partition a finite set of elements, each associated with a d-vector, into p disjoint parts so as to optimize an objective, which depends on the averages of the vectors that are assigned to each of the parts. Each partition is then associated with a d x p matrix whose columns are the corresponding averages and a useful approach in studying the problem is to explore the mean-partition polytope, defined as the convex hull of the set of matrices associated with feasible partitions.en_US
dc.identifier.doi10.1007/s10898-006-9025-0en_US
dc.identifier.issn0925-5001en_US
dc.identifier.journalJOURNAL OF GLOBAL OPTIMIZATIONen_US
dc.identifier.urihttp://dx.doi.org/10.1007/s10898-006-9025-0en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/11891
dc.identifier.wosnumberWOS:000239729700002
dc.language.isoen_USen_US
dc.subjectpartition problemsen_US
dc.subjectcombinatorial optimizationen_US
dc.subjectmeansen_US
dc.titleThe mean-partition problemen_US
dc.typeArticleen_US

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