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Stochastic Online Scheduling Revisited

机译:重新探讨随机在线计划

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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 novel linear programming relaxation for stochastic scheduling problems, which can be solved online.
机译:当作业具有随机处理时间并且可能随时间到达时,我们考虑使相同并行机上的总加权完成时间最小化的问题。我们提供了随机,确定性的在线和离线算法,这些算法在设置,确定性和离线或随机和在线中均具有最著名的性能保证。我们的分析基于一种新颖的线性规划松弛方法,可以解决在线随机调度问题。

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