Approximation Results for Preemptive Stochastic Online Scheduling
AbstractWe present first constant performance guarantees for preemptive stochastic scheduling to minimize the sum of weighted completion times. For scheduling jobs with release dates on identical parallel machines we derive policies with a guaranteed performance ratio of 2 which matches the currently best known result for the corresponding deterministic online problem. Our policies apply to the recently introduced stochastic online scheduling model inwhich jobs arrive online over time. In contrast to the previously considered nonpreemptivesetting, our preemptive policies extensively utilize information on processing time distributions other than the first (and second) moments. In order to derive our results we introduce a new nontrivial lower bound on the expected value of an unknown optimal policy that we derive from an optimal policy for the basic problem on a single machine without release dates. This problem is known to be solved optimally by a Gittins index priority rule. This priority index also inspires the design of our policies.
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Bibliographic InfoPaper provided by Maastricht : METEOR, Maastricht Research School of Economics of Technology and Organization in its series Research Memoranda with number 053.
Date of creation: 2006
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Web page: http://www.maastrichtuniversity.nl/web/UMPublications.htm
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- repec:ner:maastr:urn:nbn:nl:ui:27-5884 is not listed on IDEAS
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- Marbán Sebastián & Rutten Cyriel & Vredeveld Tjark, 2010. "Tight performance in Bayesian Scheduling," Research Memoranda 052, Maastricht : METEOR, Maastricht Research School of Economics of Technology and Organization.
- Marbán Sebastián & Rutten Cyriel & Vredeveld Tjark, 2010. "Asymptotic optimality of SEPT in Bayesian Scheduling," Research Memoranda 051, Maastricht : METEOR, Maastricht Research School of Economics of Technology and Organization.
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