103,034 research outputs found
On three domination numbers in block graphs
The problems of determining minimum identifying, locating-dominating or open
locating-dominating codes are special search problems that are challenging both
from a theoretical and a computational point of view. Hence, a typical line of
attack for these problems is to determine lower and upper bounds for minimum
codes in special graphs. In this work we study the problem of determining the
cardinality of minimum codes in block graphs (that are diamond-free chordal
graphs). We present for all three codes lower and upper bounds as well as block
graphs where these bounds are attained
Identifying codes in vertex-transitive graphs and strongly regular graphs
We consider the problem of computing identifying codes of graphs and its fractional relaxation. The ratio between the size of optimal integer and fractional solutions is between 1 and 2ln(vertical bar V vertical bar) + 1 where V is the set of vertices of the graph. We focus on vertex-transitive graphs for which we can compute the exact fractional solution. There are known examples of vertex-transitive graphs that reach both bounds. We exhibit infinite families of vertex-transitive graphs with integer and fractional identifying codes of order vertical bar V vertical bar(alpha) with alpha is an element of{1/4, 1/3, 2/5}These families are generalized quadrangles (strongly regular graphs based on finite geometries). They also provide examples for metric dimension of graphs
Random subgraphs make identification affordable
An identifying code of a graph is a dominating set which uniquely determines
all the vertices by their neighborhood within the code. Whereas graphs with
large minimum degree have small domination number, this is not the case for the
identifying code number (the size of a smallest identifying code), which indeed
is not even a monotone parameter with respect to graph inclusion.
We show that every graph with vertices, maximum degree
and minimum degree , for some
constant , contains a large spanning subgraph which admits an identifying
code with size . In particular, if
, then has a dense spanning subgraph with identifying
code , namely, of asymptotically optimal size. The
subgraph we build is created using a probabilistic approach, and we use an
interplay of various random methods to analyze it. Moreover we show that the
result is essentially best possible, both in terms of the number of deleted
edges and the size of the identifying code
Improved Bounds for -Identifying Codes of the Hex Grid
For any positive integer , an -identifying code on a graph is a set
such that for every vertex in , the intersection of the
radius- closed neighborhood with is nonempty and pairwise distinct. For
a finite graph, the density of a code is , which naturally extends
to a definition of density in certain infinite graphs which are locally finite.
We find a code of density less than , which is sparser than the prior
best construction which has density approximately .Comment: 12p
Solving Two Conjectures regarding Codes for Location in Circulant Graphs
Identifying and locating-dominating codes have been widely studied in
circulant graphs of type , which can also be viewed as
power graphs of cycles. Recently, Ghebleh and Niepel (2013) considered
identification and location-domination in the circulant graphs . They
showed that the smallest cardinality of a locating-dominating code in
is at least and at most
for all . Moreover, they proved that the lower bound is strict when
and conjectured that the lower bound can be
increased by one for other . In this paper, we prove their conjecture.
Similarly, they showed that the smallest cardinality of an identifying code in
is at least and at most for all . Furthermore, they proved that the lower bound is
attained for most of the lengths and conjectured that in the rest of the
cases the lower bound can improved by one. This conjecture is also proved in
the paper. The proofs of the conjectures are based on a novel approach which,
instead of making use of the local properties of the graphs as is usual to
identification and location-domination, also manages to take advantage of the
global properties of the codes and the underlying graphs
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