Models and Algorithms for Stochastic Online Scheduling

dc.contributor.authorMegow, Nicole
dc.contributor.authorUetz, Marc
dc.contributor.authorVredeveld, Tjark
dc.date.accessioned2021-12-17T10:06:41Z
dc.date.available2021-12-17T10:06:41Z
dc.date.issued2005
dc.description.abstractWe introduce a model for scheduling under uncertainty. In this model, we combine the main characteristics of online and stochastic scheduling in a simple and natural way. Job processing times are assumed to be stochastic, but in contrast to traditional stochastic scheduling models, we assume that jobs arrive online, and there is no knowledge about the jobs that will arrive in the future. The model incorporates both, stochastic scheduling and online scheduling as a special case. The particular setting we analyze is nonpreemptive parallel machine scheduling, with the objective to minimize the total weighted completion times of jobs. We propose simple, combinatorial online scheduling policies for that model, and derive performance guarantees that match the currently best known performance guarantees for stochastic and online parallel machine scheduling. For processing times that follow NBUE distributions, we improve upon previously best known performance bounds from stochastic scheduling, even though we consider a more general setting.en
dc.identifier.issn2197-8085
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/15574
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-14347
dc.language.isoenen
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject.ddc510 Mathematiken
dc.subject.otherstochastic schedulingen
dc.subject.otheronline schedulingen
dc.subject.otheraverage completion timeen
dc.subject.otherpoliciesen
dc.titleModels and Algorithms for Stochastic Online Schedulingen
dc.typeResearch Paperen
dc.type.versionsubmittedVersionen
tub.accessrights.dnbfreeen
tub.affiliationFak. 2 Mathematik und Naturwissenschaften::Inst. Mathematikde
tub.affiliation.facultyFak. 2 Mathematik und Naturwissenschaftende
tub.affiliation.instituteInst. Mathematikde
tub.publisher.universityorinstitutionTechnische Universität Berlinen
tub.series.issuenumber2005, 03en
tub.series.namePreprint-Reihe des Instituts für Mathematik, Technische Universität Berlinen
tub.subject.msc200090B36 Scheduling theory, stochasticen
tub.subject.msc200068W40 Analysis of algorithmsen
tub.subject.msc200068W25 Approximation algorithmsen
tub.subject.msc200068M20 Performance evaluation; queueing; schedulingen

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