round - up和ROUND-SAP的近似算法

Debajyoti Kar, Arindam Khan, Andreas Wiese
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引用次数: 1

摘要

本文研究了经典BIN PACKING问题的两种推广,分别对应于路径上不可分割流问题(UFP)和存储分配问题(SAP)的ROUND-UFP和ROUND-SAP。我们有一条边有容量的路径和一组任务,每个任务我们都有一个需求和一个子路径。在ROUND-UFP中,目标是将所有任务打包成给定路径的最小拷贝数(轮数),使得对于每个拷贝,任何边缘上的任务总需求不超过各自边缘的容量。在ROUND-SAP中,任务被认为是矩形,目标是找到这些矩形的非重叠包装成最小数量的轮,以便所有矩形完全位于边缘的容量轮廓之下。我们表明,与BIN PACKING相比,这两个问题都不承认渐近多项式时间逼近格式(APTAS),即使当所有边容量相等时。然而,对于这个设置,我们得到了两个问题的渐近$(2+\varepsilon)$ -逼近。对于一般情况,我们得到了两个问题的$O(\log\log n)$ -逼近算法和$(1+\delta)$ -资源增加下的$O(\log\log\frac{1}{\delta})$ -逼近算法。对于无瓶颈假设的中间设置(即最大任务需求最多是最小边缘容量),我们分别获得了ROUND-UFP和ROUND-SAP的绝对$12$ -近似算法和渐近$(16+\varepsilon)$ -近似算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Approximation Algorithms for ROUND-UFP and ROUND-SAP
We study ROUND-UFP and ROUND-SAP, two generalizations of the classical BIN PACKING problem that correspond to the unsplittable flow problem on a path (UFP) and the storage allocation problem (SAP), respectively. We are given a path with capacities on its edges and a set of tasks where for each task we are given a demand and a subpath. In ROUND-UFP, the goal is to find a packing of all tasks into a minimum number of copies (rounds) of the given path such that for each copy, the total demand of tasks on any edge does not exceed the capacity of the respective edge. In ROUND-SAP, the tasks are considered to be rectangles and the goal is to find a non-overlapping packing of these rectangles into a minimum number of rounds such that all rectangles lie completely below the capacity profile of the edges. We show that in contrast to BIN PACKING, both the problems do not admit an asymptotic polynomial-time approximation scheme (APTAS), even when all edge capacities are equal. However, for this setting, we obtain asymptotic $(2+\varepsilon)$-approximations for both problems. For the general case, we obtain an $O(\log\log n)$-approximation algorithm and an $O(\log\log\frac{1}{\delta})$-approximation under $(1+\delta)$-resource augmentation for both problems. For the intermediate setting of the no bottleneck assumption (i.e., the maximum task demand is at most the minimum edge capacity), we obtain absolute $12$- and asymptotic $(16+\varepsilon)$-approximation algorithms for ROUND-UFP and ROUND-SAP, respectively.
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