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A PTAS for Minimizing Weighted Completion Time on Uniformly Related Machines

机译:PTAS,用于最小化统一关联机器上的加权完成时间

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We consider the well known problem of scheduling jobs with release dates to minimize their average weighted completion time. When multiple machines are available, the machine environment may range from identical machines (the processing time required by a job is invariant across the machines) at one end of the spectrum to unrelated machines (the processing time required by a job on each machine is specified by an arbitrary vector) at the other end. While the problem is strongly NP-hard even in the case of a single machine, constant factor approximation algorithms are known for even the most general machine environment of unrelated machines. Recently a PTAS was discovered for the case of identical parallel machines. In contrast, the problem is MAX SNP-hard for unrelated machines. An important open problem was to determine the approximability of the intermediate case of uniformly related machines where each machine has a speed and it takes p/s time to process a job of size p on a machine with speed s. We resolve the complexity of this problem by obtaining a PTAS. This improves the earlier known approximation ratio of (2 + ε).
机译:我们考虑一个众所周知的问题,即计划具有发布日期的作业以最大程度地减少其平均加权完成时间。当有多台机器可用时,机器环境的范围可能从频谱一端的同一台机器(作业所需的处理时间在各台机器上是不变的)到不相关的机器(指定了每台机器上作业所需的处理时间)在另一端)。尽管即使在单台机器的情况下,该问题也对NP来说非常困难,但对于不相关机器的最一般机器环境,恒定因子近似算法也是众所周知的。最近,对于相同的并行机,发现了PTAS。相反,问题是不相关机器的MAX SNP很难。一个重要的开放性问题是确定均匀关联的机器的中间情况的近似性,在该情况下,每台机器都有一个速度,并且在速度为s的机器上处理大小为p的作业要花费p / s的时间。我们通过获取PTAS解决了此问题的复杂性。这提高了先前已知的近似比率(2 +ε)。

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