论文标题
平面和和弦图上的大地测量集算法和复杂性
Algorithms and complexity for geodetic sets on planar and chordal graphs
论文作者
论文摘要
我们研究了在平面图和弦图的子类上找到\ emph {Geodetic数字}的复杂性。如果$ g $的每个顶点处于$ s $的一对顶点之间的最短路径,则图$ g $的$ s $是a \ emph {Geodetic set}。 \ textsc {最小测量集(MGS)}问题是找到一个给定图的最小基数的大地测量集。已知该问题在二分图,弦图,平面图和亚立管图上仍然保持NP-螺态。我们首先在限制的平面图类别上研究\ textsc {mgs}:我们在固体网格上为\ textsc {mgs}设计了线性时间算法,在Chakraborty等人的$ 3 $ - APPROXIMATION算法上改进了。 (Caldam,2020年),并表明它仍然是NP-HARD,即使对于任意腰带的亚皮的部分网格也是如此。这统一了文献中的一些结果。然后,我们将注意力转向和弦图,表明当通过其\ emph {tree-width}参数化时,\ textsc {mgs}是固定的参数可用于该类的输入(等于其集团数字)。这意味着$ k $树的多项式时间算法,用于固定的$ k $。然后,我们证明\ textsc {mgs}是间隔图上的np-hard,从而回答了Ekim等人的问题。 (Latin,2012)。由于间隔图受到非常限制,为了证明后者的结果,我们设计了一种相当复杂的还原技术来围绕其固有的线性结构工作。
We study the complexity of finding the \emph{geodetic number} on subclasses of planar graphs and chordal graphs. A set $S$ of vertices of a graph $G$ is a \emph{geodetic set} if every vertex of $G$ lies in a shortest path between some pair of vertices of $S$. The \textsc{Minimum Geodetic Set (MGS)} problem is to find a geodetic set with minimum cardinality of a given graph. The problem is known to remain NP-hard on bipartite graphs, chordal graphs, planar graphs and subcubic graphs. We first study \textsc{MGS} on restricted classes of planar graphs: we design a linear-time algorithm for \textsc{MGS} on solid grids, improving on a $3$-approximation algorithm by Chakraborty et al. (CALDAM, 2020) and show that it remains NP-hard even for subcubic partial grids of arbitrary girth. This unifies some results in the literature. We then turn our attention to chordal graphs, showing that \textsc{MGS} is fixed parameter tractable for inputs of this class when parameterized by its \emph{tree-width} (which equals its clique number). This implies a polynomial-time algorithm for $k$-trees, for fixed $k$. Then, we show that \textsc{MGS} is NP-hard on interval graphs, thereby answering a question of Ekim et al. (LATIN, 2012). As interval graphs are very constrained, to prove the latter result we design a rather sophisticated reduction technique to work around their inherent linear structure.