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On the Robustness of Graham’s Algorithm for Online Scheduling

机译:论格雷厄姆在线调度算法的鲁棒性

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While standard parallel machine scheduling is concerned with good assignments of jobs to machines, we aim to understand how the quality of an assignment is affected if the jobs’ processing times are perturbed and therefore turn out to be longer (or shorter) than declared. We focus on online scheduling with perturbations occurring at any time, such as in railway systems when trains are late. For a variety of conditions on the severity of perturbations, we present upper bounds on the worst case ratio of two makespans. For the first makespan, we let Graham’s algorithm assign jobs to machines, based on the non-perturbed processing times. We compute the makespan by replacing each job’s processing time with its perturbed version while still sticking to the computed assignment. The second is an optimal offline solution for the perturbed processing times. The deviation of this ratio from Graham’s competitive ratio (of slightly less than 2) tells us about the “price of perturbations”. For instance, we show a competitive ratio of 2 for perturbations decreasing the processing time of a job arbitrarily, and a competitive ratio of less than 2.5 for perturbations doubling the processing time of a job.
机译:虽然标准并行机器调度涉及到机器的良好作业分配,但我们的目标是了解如果作业的处理时间扰乱,则会了解分配的质量如何受到影响,因此结果比声明更长(或更短)。我们专注于在线调度随时随地发生的扰动,例如在火车晚期的铁路系统中进行。对于扰动严重程度的各种条件,我们在两个MakEspans的最坏情况下呈现上限。对于第一个MakEspan,我们让Graham的算法基于非扰动的处理时间将作业分配给机器。我们通过使用其扰动版本替换每个作业的处理时间来计算MakeSpan,同时仍然粘附到计算的分配。第二个是扰动处理时间的最佳离线解决方案。该比例与格雷厄姆竞争比率(略低于2)告诉我们“扰动价格”。例如,我们显示出扰动的竞争比例是扰动任意减少作业的处理时间,并且对于工作的处理时间加倍,扰动的竞争比例小于2.5。

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