顶点删除问题的紧运行时间下界

Christian Komusiewicz
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引用次数: 11

摘要

对于一个图类Π, Π-Vertex删除问题有一个无向图G = (V,E)和一个整数k作为输入,并询问是否存在一个最多k个顶点的集合,可以从G中删除,使得结果图是Π的成员。根据Lewis和Yannakakis[17]的经典结果,Π-Vertex对于所有遗传特性来说,缺失都是NP-hard的Π。我们对原来的np -硬度结构进行了调整,证明在指数时间假设(ETH)下,可以得到紧复杂度的结果。我们证明Π-Vertex删除不允许20 (n)时间算法,其中n是g中的顶点数。我们还获得了包含输入图中边数m的运行时间界限的二分类。一方面,如果Π包含所有无边图,则不存在耗时20 (n+m)的Π-Vertex delete算法。另一方面,如果存在一个不包含在Π中的固定无边图,并且在20 (n)或20 (m)时间内可以确定Π中的包含,则Π-Vertex的删除可以分别在20(√m)+O(n)或20 (m)+O(n)时间内解决。我们还考虑了输入图G的域上的限制,例如,我们得到了Π-Vertex不能在20(√n)时间内解决删除,如果G是平面的,Π是遗传的,包含和排除无限多个平面图。最后,对于删除的顶点集必须生成连通图的问题变体,我们提供了类似的结果。
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Tight Running Time Lower Bounds for Vertex Deletion Problems
For a graph class Π, the Π-Vertex Deletion problem has as input an undirected graph G = (V,E) and an integer k and asks whether there is a set of at most k vertices that can be deleted from G such that the resulting graph is a member of Π. By a classic result of Lewis and Yannakakis [17], Π-Vertex Deletion is NP-hard for all hereditary properties Π. We adapt the original NP-hardness construction to show that under the exponential time hypothesis (ETH), tight complexity results can be obtained. We show that Π-Vertex Deletion does not admit a 2o(n)-time algorithm where n is the number of vertices in G. We also obtain a dichotomy for running time bounds that include the number m of edges in the input graph. On the one hand, if Π contains all edgeless graphs, then there is no 2o(n+m)-time algorithm for Π-Vertex Deletion. On the other hand, if there is a fixed edgeless graph that is not contained in Π and containment in Π can be determined in 2O(n) time or 2o(m) time, then Π-Vertex Deletion can be solved in 2O(√m)+O(n) or 2o(m)+O(n) time, respectively. We also consider restrictions on the domain of the input graph G. For example, we obtain that Π-Vertex Deletion cannot be solved in 2o(√n) time if G is planar and Π is hereditary and contains and excludes infinitely many planar graphs. Finally, we provide similar results for the problem variant where the deleted vertex set has to induce a connected graph.
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