Stochastic online scheduling
نویسندگان
چکیده
منابع مشابه
Stochastic Online Scheduling Revisited
We consider the problem of minimizing the total weighted completion time on identical parallel machines when jobs have stochastic processing times and may arrive over time. We give randomized as well as deterministic online and off-line algorithms that have the best known performance guarantees in either setting, deterministic and offline or randomized and online. Our analysis is based on a nov...
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We consider 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 mod...
متن کاملApproximation in Preemptive Stochastic Online Scheduling
We present a first constant performance guarantee for preemptive stochastic scheduling to minimize the sum of weighted completion times. For scheduling jobs with release dates on identical parallel machines we derive a policy with a guaranteed performance ratio of 2 which matches the currently best known result for the corresponding deterministic online problem. Our policy applies to the recent...
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The effective management of a cancer treatment facility for radiation therapy depends mainly on optimizing the use of the linear accelerators. In this project, we schedule patients on these machines taking into account their priority for treatment, the maximum waiting time before the first treatment, and the treatment duration. We collaborate with the Centre Intégré de Cancérologie de Laval to ...
متن کاملAsymptotic Results On Stochastic Online Scheduling Problems
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.
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ژورنال
عنوان ژورنال: Computer Science - Research and Development
سال: 2011
ISSN: 1865-2034,1865-2042
DOI: 10.1007/s00450-011-0153-5