Tight Algorithmic Applications of Clique-Width Generalizations

V. Chekan, Stefan Kratsch
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Abstract

In this work, we study two natural generalizations of clique-width introduced by Martin F\"urer. Multi-clique-width (mcw) allows every vertex to hold multiple labels [ITCS 2017], while for fusion-width (fw) we have a possibility to merge all vertices of a certain label [LATIN 2014]. F\"urer has shown that both parameters are upper-bounded by treewidth thus making them more appealing from an algorithmic perspective than clique-width and asked for applications of these parameters for problem solving. First, we determine the relation between these two parameters by showing that $\operatorname{mcw} \leq \operatorname{fw} + 1$. Then we show that when parameterized by multi-clique-width, many problems (e.g., Connected Dominating Set) admit algorithms with the same running time as for clique-width despite the exponential gap between these two parameters. For some problems (e.g., Hamiltonian Cycle) we show an analogous result for fusion-width: For this we present an alternative view on fusion-width by introducing so-called glue-expressions which might be interesting on their own. All algorithms obtained in this work are tight up to (Strong) Exponential Time Hypothesis.
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团宽推广的严密算法应用
在这项工作中,我们研究了Martin f rer引入的两个自然推广的团宽度。Multi-clique-width (mcw)允许每个顶点持有多个标签[ITCS 2017],而对于融合宽度(fw),我们有可能合并某个标签的所有顶点[LATIN 2014]。f rer已经表明,这两个参数都是树宽度的上限,因此从算法的角度来看,它们比团宽度更有吸引力,并要求将这些参数应用于问题解决。首先,我们通过显示$\operatorname{mcw} \leq \operatorname{fw} + 1$来确定这两个参数之间的关系。然后我们证明了当参数化为多团宽度时,许多问题(例如连通支配集)允许算法与团宽度具有相同的运行时间,尽管这两个参数之间存在指数差距。对于某些问题(例如,哈密顿循环),我们给出了关于融合宽度的类似结果:为此,我们提出了关于融合宽度的另一种观点,通过引入所谓的粘合表达式,它本身可能很有趣。本研究中得到的所有算法都符合(强)指数时间假设。
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