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Conference Paper: Asymptotic results on stochastic online scheduling problems

TitleAsymptotic results on stochastic online scheduling problems
Authors
Chen, GShen, Z
Issue Date19-May-2004
Abstract

We consider a stochastic online scheduling environment, where jobs with stochastic processing requirements arrive over time and the objective is to minimize the total weighted completion time. We show that any nondelay algorithm is asymptotically optimal for the stochastic online single machine, flow shop and uniform parallel machine problems under some mild assumptions.


Persistent Identifierhttp://hdl.handle.net/10722/369455

 

DC FieldValueLanguage
dc.contributor.authorChen, G-
dc.contributor.authorShen, Z-
dc.date.accessioned2026-01-24T00:35:15Z-
dc.date.available2026-01-24T00:35:15Z-
dc.date.issued2004-05-19-
dc.identifier.urihttp://hdl.handle.net/10722/369455-
dc.description.abstract<p>We consider a stochastic online scheduling environment, where jobs with stochastic processing requirements arrive over time and the objective is to minimize the total weighted completion time. We show that any nondelay algorithm is asymptotically optimal for the stochastic online single machine, flow shop and uniform parallel machine problems under some mild assumptions.</p>-
dc.languageeng-
dc.relation.ispartofIIE Annual Conference and Exhibition 2004 (15/05/2004-19/05/2004)-
dc.titleAsymptotic results on stochastic online scheduling problems-
dc.typeConference_Paper-

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