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arXiv 1802.09801cs.DM
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广义图着色和均匀拟白度的近似算法的经验评价

Empirical Evaluation of Approximation Algorithms for Generalized Graph Coloring and Uniform Quasi-Wideness

Wojciech Nadara, Marcin Pilipczuk, Roman Rabinovich, Felix Reidl, Sebastian Siebertz

摘要:

有界扩张和无处稠密的概念不仅提供了图的一致稀疏性的鲁棒和一般的定义,它们还描述了几个重要算法问题的易处理边界。在本文中,我们研究了这些图类的两个结构性质是特别重要的,在这种情况下,即属性有界广义染色数和属性的一致准宽。我们提供了几个算法的实验评估,近似这些参数在现实世界的图形。在理论方面,我们提供了一个新的算法,统一的准宽度与多项式大小的保证,在有界扩展的图形类,并显示了一个下界表明,该算法的保证是接近最佳的图形类与固定的排除未成年人。

英文摘要:

The notions of bounded expansion and nowhere denseness not only offer robust and general definitions of uniform sparseness of graphs, they also describe the tractability boundary for several important algorithmic questions. In this paper we study two structural properties of these graph classes that are of particular importance in this context, namely the property of having bounded generalized coloring numbers and the property of being uniformly quasi-wide. We provide experimental evaluations of several algorithms that approximate these parameters on real-world graphs. On the theoretical side, we provide a new algorithm for uniform quasi-wideness with polynomial size guarantees in graph classes of bounded expansion and show a lower bound indicating that the guarantees of this algorithm are close to optimal in graph classes with fixed excluded minor.

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。

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