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3-Paths in Graphs with Bounded Average Degree

100%
Jendrol′ S., Maceková M., Montassier M., Soták R.
Discussiones Mathematicae Graph Theory
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2016
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tom 36
|
nr 2
339-353
EN
In this paper we study the existence of unavoidable paths on three vertices in sparse graphs. A path uvw on three vertices u, v, and w is of type (i, j, k) if the degree of u (respectively v, w) is at most i (respectively j, k). We prove that every graph with minimum degree at least 2 and average degree strictly less than m contains a path of one of the types [...] Moreover, no parameter of this description can be improved.
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On double domination in graphs

100%
Harant J., Henning M.
Discussiones Mathematicae Graph Theory
|
2005
|
tom 25
|
nr 1-2
29-34
EN
In a graph G, a vertex dominates itself and its neighbors. A subset S ⊆ V(G) is a double dominating set of G if S dominates every vertex of G at least twice. The minimum cardinality of a double dominating set of G is the double domination number $γ_{×2}(G)$. A function f(p) is defined, and it is shown that $γ_{×2}(G) = min f(p)$, where the minimum is taken over the n-dimensional cube $Cⁿ = {p = (p₁,...,pₙ) | p_i ∈ IR, 0 ≤ p_i ≤ 1,i = 1,...,n}$. Using this result, it is then shown that if G has order n with minimum degree δ and average degree d, then $γ_{×2}(G) ≤ ((ln(1+d) + lnδ + 1)/δ)n$.
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An advance in infinite graph models for the analysis of transportation networks

88%
Cera M., Fedriani E.
International Journal of Applied Mathematics and Computer Science
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2016
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tom 26
|
nr 4
855-870
EN
This paper extends to infinite graphs the most general extremal issues, which are problems of determining the maximum number of edges of a graph not containing a given subgraph. It also relates the new results with the corresponding situations for the finite case. In particular, concepts from ‘finite' graph theory, like the average degree and the extremal number, are generalized and computed for some specific cases. Finally, some applications of infinite graphs to the transportation of dangerous goods are presented; they involve the analysis of networks and percolation thresholds.
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