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Article . 2021 . Peer-reviewed
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Article . 2021
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Rainbow vertex connection number and strong rainbow vertex connection number on slinky graph (SlnC4))

Authors: Afifah Farhanah Akadji; Muhammad Rifai Katili; Salmun K. Nasib; Nisky Imansyah Yahya;

Rainbow vertex connection number and strong rainbow vertex connection number on slinky graph (SlnC4))

Abstract

A graph is said rainbow connected if no path has more than one vertices of the same color inside. The minimum number of colors required to make a graph to be rainbow vertex-connected is called rainbow vertex connection-number and denoted by rvc(G) . Meanwhile, the minimum number of colors required to make a graph to be strongly rainbow vertex-connected is called strong rainbow vertex connection-number and denoted by srvc(G). Suppose there is a simple, limited, and finite graph G. Thus, G=(V(G),E(G)) with the determination of k-coloring c:V(G)->{1,2,...,k} . The reaserch aims at determining rainbow vertex connection-number and strong rainbow vertex connection-number on slinky graphs (Sl_nC_4). Moreover, the research method applies a literature study with the following procedures; drawing slinky graphs (Sl_nC_4), looking for patterns of rainbow vertex connection-number, and strong rainbow vertex connection-number on slinky graphs (Sl_nC_4), then proving the theorems obtained from the previous pattern. It is obtained rvc(Sl_nC_4)=2n-1, srvc(Sl_2C_4)=4, and srvc(Sl_nC_4) = 3n-3 for n>= 3. 

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Keywords

T57-57.97, Applied mathematics. Quantitative methods, rainbow vertex connection, strong rainbow vertex connection, QA1-939, graph, slinky graph, Mathematics

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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!
0
Average
Average
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