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Theoretical Computer Science
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Theoretical Computer Science
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Further hardness results on the rainbow vertex-connection number of graphs

Authors: Lily Chen; Xueliang Li 0001; Huishu Lian;

Further hardness results on the rainbow vertex-connection number of graphs

Abstract

A vertex-colored graph $G$ is {\it rainbow vertex-connected} if any pair of vertices in $G$ are connected by a path whose internal vertices have distinct colors, which was introduced by Krivelevich and Yuster. The {\it rainbow vertex-connection number} of a connected graph $G$, denoted by $rvc(G)$, is the smallest number of colors that are needed in order to make $G$ rainbow vertex-connected. In a previous paper we showed that it is NP-Complete to decide whether a given graph $G$ has $rvc(G)=2$. In this paper we show that for every integer $k\geq 2$, deciding whether $rvc(G)\leq k$ is NP-Hard. We also show that for any fixed integer $k\geq 2$, this problem belongs to NP-class, and so it becomes NP-Complete.

10 pages

Related Organizations
Keywords

FOS: Computer and information sciences, Connectivity, NP-hard, Computational Complexity (cs.CC), vertex-colored graph, rainbow vertex-connection number, Computer Science - Computational Complexity, Coloring of graphs and hypergraphs, FOS: Mathematics, Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.), Mathematics - Combinatorics, 05C15, 05C40, 68Q17, 68Q25, 90C27, Combinatorics (math.CO), NP-complete

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Top 10%
Top 10%
Green
hybrid