最小熵定向
Minimum Entropy Orientations
摘要:
我们研究图的方向,最小化的熵的度序列。找到这样一个方向的问题是一个有趣的特殊情况下的最小熵集覆盖问题以前研究的Halperin和Karp [TheoreticComput.科学,[2005]和目前的作者[马云,出现]。我们证明了最小熵方向问题是NP-难的,即使图形是平面的,并且存在一个简单的线性时间算法,该算法返回一个近似的解决方案,具有1位的附加误差保证。这改进了仅有的先前已知的算法,该算法具有log_2 e比特的附加误差保证(约100比特)。1.4427比特)。
英文摘要:
We study graph orientations that minimize the entropy of the in-degree sequence. The problem of finding such an orientation is an interesting special case of the minimum entropy set cover problem previously studied by Halperin and Karp [Theoret. Comput. Sci., 2005] and by the current authors [Algorithmica, to appear]. We prove that the minimum entropy orientation problem is NP-hard even if the graph is planar, and that there exists a simple linear-time algorithm that returns an approximate solution with an additive error guarantee of 1 bit. This improves on the only previously known algorithm which has an additive error guarantee of log_2 e bits (approx. 1.4427 bits).
机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。