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An Improved Approximation for Scheduling Malleable Tasks with Precedence Constraints via Iterative Method

机译:具有优先约束的可延展任务的迭代迭代逼近

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The problem of scheduling malleable tasks with precedence constraints is one of the most important strongly NP-hard problems, given m identical processors and n tasks. A malleable task is one that runs in parallel on a varying number of processors. In addition, the processing sequences of tasks are constrained by the precedence constraints. The goal is to find a feasible schedule that minimizes the makespan (maximum completion time). This article presents an iterative method for improving the performance ratio of scheduling malleable tasks. The proposed algorithm achieves an approximation ratio of 4.4841 after 2 iterations. This improves the so far best-known factor of 4.7306 due to Jansen and Zhang. For a large number of iterations (> 100), the approximation ratio of the proposed algorithm is tends toward 2 + √2 ≈ 3.4143.
机译:给定m个相同的处理器和n个任务,调度具有优先级约束的可延展任务的问题是最重要的强NP难题。可延展任务是在不同数量的处理器上并行运行的任务。另外,任务的处理顺序受到优先约束的约束。目的是找到一个可行的时间表,以最大程度地减少工期(最大完成时间)。本文提出了一种迭代方法,可提高调度可延展任务的性能比。所提出的算法经过2次迭代后达到了4.4841的近似率。由于Jansen和Zhang,这改善了迄今为止最著名的系数4.7306。对于大量的迭代(> 100),所提出算法的近似率趋于2 +√2≈3.4143。

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