Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/632
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dc.contributorDepartment of Logistics and Maritime Studies-
dc.creatorCheng, TCE-
dc.creatorKellerer, H-
dc.creatorKotov, V-
dc.date.accessioned2014-12-11T08:24:42Z-
dc.date.available2014-12-11T08:24:42Z-
dc.identifier.issn0304-3975-
dc.identifier.urihttp://hdl.handle.net/10397/632-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rightsTheoretical Computer Science © 2005 Elsevier B.V. The journal web site is located at http://www.sciencedirect.com.en_US
dc.subjectOn-line algorithmsen_US
dc.subjectSemi-on-line algorithmsen_US
dc.subjectBin stretchingen_US
dc.subjectMultiprocessor schedulingen_US
dc.subjectApproximation algorithmsen_US
dc.titleSemi-on-line multiprocessor scheduling with given total processing timeen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage134-
dc.identifier.epage146-
dc.identifier.volume337-
dc.identifier.issue1-3-
dc.identifier.doi10.1016/j.tcs.2004.11.018-
dcterms.abstractWe are given a set of identical machines and a sequence of jobs, the sum of whose weights is known in advance. The jobs are to be assigned on-line to one of the machines and the objective is to minimize the makespan. An algorithm with performance ratio 1.6 and a lower bound of 1.5 is presented. These results improve on the recent results by Azar and Regev, who proposed an algorithm with performance ratio 1.625 for the less general problem that the optimal makespan is known in advance.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationTheoretical computer science, June 2005, v. 337, no. 1-3, p. 134-146-
dcterms.isPartOfTheoretical computer science-
dcterms.issued2005-06-
dc.identifier.isiWOS:000229668700005-
dc.identifier.scopus2-s2.0-18444407803-
dc.identifier.rosgroupidr22924-
dc.description.ros2004-2005 > Academic research: refereed > Publication in refereed journal-
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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