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Performance Guarantees for Scheduling Algorithms under Perturbed Machine Speeds

机译:扰动机速度下的调度算法的性能保证

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We study two local search and a greedy algorithm for scheduling. The worst-case performance guarantees are well-known but seem to be contrived and too pessimistic for practical applications. For unrestricted machines, Brunsch et al. [3] showed that the worst-case performance guarantees of these algorithms are not robust if the job sizes are subject to random noise. However, in the case of restricted related machines the worst-case bounds turned out to be robust even in the presence of random noise. We show that if the machine speeds rather than the job sizes are perturbed, also the performance guarantees for restricted machines decrease thus yielding a stronger result.
机译:我们研究了两个本地搜索和贪婪算法进行调度。最糟糕的性能保证是众所周知的,但似乎是实际应用的悲观和太悲观。对于不受限制的机器,Brunsch等人。 [3]显示,如果作业大小受到随机噪声,则这些算法的最坏情况性能保证是不稳定的。然而,在限制相关机器的情况下,即使在随机噪声存在下,也使最坏情况界限变得坚固。我们表明,如果机器速度而不是工作尺寸扰乱,则限制机器的性能保证也降低了,因此产生了更强的结果。

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