Bamboo Trimming Revisited: Simple Algorithms Can Do Well Too

John Kuszmaul
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引用次数: 2

Abstract

The bamboo trimming problem considers n bamboo with growth rates h1, 2, . . . , satisfying Σihi = 1. During a given unit of time, each bamboo grows by hi , and then the bamboo-trimming algorithm gets to trim one of the bamboo back down to height zero. The goal is to minimize the height of the tallest bamboo, also known as the backlog. The bamboo trimming problem is closely related to many scheduling problems, and can be viewed as a variation of the widely-studied fixed-rate cup game, but with constant-factor resource augmentation. Past work has given sophisticated pinwheel algorithms that achieve the optimal backlog of 2 in the bamboo trimming problem. It remained an open question, however, whether there exists a simple algorithm with the same guarantee-recent work has devoted considerable theoretical and experimental effort to answering this question. Two algorithms, in particular, have appeared as natural candidates: the Reduce-Max algorithm (which always cuts the tallest bamboo) and the Reduce-Fastest(x) algorithm (which cuts the fastest-growing bamboo out of those that have at least some height x). It is conjectured that Reduce-Max and Reduce- Fastest(1) both achieve backlog 2. This paper improves the bounds for both Reduce-Fastest and Reduce-Max. Among other results, we show that the exact optimal backlog for Reduce-Fastest(x) is x + 1 for all x ≥ 2 (this proves a conjecture of D'Emidio, Di Stefano, and Navarra in the case of x = 2), and we show that Reduce-Fastest(1) does not achieve backlog 2 (this disproves a conjecture of D'Emidio, Di Stefano, and Navarra). Finally, we show that there is a different algorithm, which we call the Deadline-Driven Strategy, that is both very simple and achieves the optimal backlog of 2. This resolves the question as to whether there exists a simple worst-case optimal algorithm for the bamboo trimming problem.
重新审视竹子修剪:简单的算法也可以做得很好
竹材修剪问题考虑n根生长速率为h1、2、…的竹材。,满足Σihi = 1。在给定的时间单位内,每根竹子长1英尺,然后竹子修剪算法会将其中一根竹子修剪回0英尺。目标是最小化最高的竹子的高度,也就是所谓的积压。竹子修剪问题与许多调度问题密切相关,可以被视为广泛研究的固定速率杯游戏的变体,但具有恒定因素的资源增加。过去的工作已经给出了复杂的风车算法,可以在竹子修剪问题中实现2的最优积压。然而,是否存在一个具有同样保证的简单算法仍然是一个悬而未决的问题——最近的工作投入了大量的理论和实验努力来回答这个问题。特别是两种算法,已经成为自然的候选者:Reduce- max算法(总是切割最高的竹子)和Reduce-Fastest(x)算法(从至少有一些高度x的竹子中切割最快的竹子)。据推测,Reduce- max和Reduce-Fastest(1)都实现了积压2。本文改进了Reduce-Fastest和Reduce-Max的界。在其他结果中,我们表明,对于所有x≥2,Reduce-Fastest(x)的确切最优积压是x + 1(这证明了x = 2情况下D'Emidio, Di Stefano和Navarra的一个猜想),并且我们表明Reduce-Fastest(1)不能实现积压2(这反驳了D'Emidio, Di Stefano和Navarra的一个猜想)。最后,我们展示了一种不同的算法,我们称之为截止日期驱动策略,它既简单又能实现2个最优积压。这就解决了是否存在简单的最坏情况最优算法的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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