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Finding Hamiltonian Cycle on Cartesian Product of a Hypotraceable Graph and a Hamiltonian Graph
 THE 25TH WORKSHOP ON COMBINATORIAL MATHEMATICS AND COMPUTATION THEORY
, 2008
"... The interconnected network is usually represented by a graph where the vertices represent processors and the edges represent links between processors. A hypotraceable graph G is a graph with no Hamiltonian path, and for any vertex v ∈ V ( G) G−v has a Hamiltonian path. This paper investigates the Ca ..."
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The interconnected network is usually represented by a graph where the vertices represent processors and the edges represent links between processors. A hypotraceable graph G is a graph with no Hamiltonian path, and for any vertex v ∈ V ( G) G−v has a Hamiltonian path. This paper investigates
The ultimate question
, 2009
"... We present a planar hypohamiltonian graph on 42 vertices and show some consequences. 1 Introduction and results A graph is called hypohamiltonian if it is not Hamiltonian but deleting any vertex gives a Hamiltonian graph. Hypohamiltonian graphs were extensively studied by Sousselier, Thomassen, Chva ..."
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We present a planar hypohamiltonian graph on 42 vertices and show some consequences. 1 Introduction and results A graph is called hypohamiltonian if it is not Hamiltonian but deleting any vertex gives a Hamiltonian graph. Hypohamiltonian graphs were extensively studied by Sousselier, Thomassen
Progress on the Traceability Conjecture for Oriented Graphs
, 2008
"... A digraph is ktraceable if each of its induced subdigraphs of order k is traceable. The Traceability Conjecture is that for k ≥ 2 every ktraceable oriented graph of order at least 2k − 1 is traceable. The conjecture has been proved for k ≤ 5. We prove that it also holds for k = 6. ..."
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A digraph is ktraceable if each of its induced subdigraphs of order k is traceable. The Traceability Conjecture is that for k ≥ 2 every ktraceable oriented graph of order at least 2k − 1 is traceable. The conjecture has been proved for k ≤ 5. We prove that it also holds for k = 6.
Repository CRAN
, 2009
"... Description Routines for simple graphs and network analysis. igraph can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality indices and much more. Depends stats ..."
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Description Routines for simple graphs and network analysis. igraph can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality indices and much more. Depends stats
License GPL (> = 2)
, 2008
"... Description Routines for simple graphs and network analysis. igraph can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality indices and much more. ..."
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Description Routines for simple graphs and network analysis. igraph can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality indices and much more.
Version 0.6.51 Date 20130227 Title Network analysis and visualization Author See AUTHORS file.
, 2013
"... Description Routines for simple graphs and network analysis. igraph can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality indices and much more. Depends stats ..."
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Description Routines for simple graphs and network analysis. igraph can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality indices and much more. Depends stats
SystemRequirements gmp, libxml2
, 2013
"... Description Routines for simple graphs and network analysis. igraph can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization,centrality indices and much more. Depends stats ..."
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Description Routines for simple graphs and network analysis. igraph can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization,centrality indices and much more. Depends stats
Imports Matrix
, 2014
"... Description Routines for simple graphs and network analysis. igraph can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality indices and much more. Depends methods ..."
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Description Routines for simple graphs and network analysis. igraph can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality indices and much more. Depends methods
Intersecting longest paths and longest cycles: A survey
 ELECTRONIC JOURNAL OF GRAPH THEORY AND APPLICATIONS 1 (1) (2013), 56–76
, 2013
"... This is a survey of results obtained during the last 45 years regarding the intersection behaviour of all longest paths, or all longest cycles, in connected graphs. Planar graphs and graphs of higher connectivity receive special attention. Graphs embeddable in the cubic lattice of arbitrary dimensio ..."
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Cited by 1 (0 self)
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This is a survey of results obtained during the last 45 years regarding the intersection behaviour of all longest paths, or all longest cycles, in connected graphs. Planar graphs and graphs of higher connectivity receive special attention. Graphs embeddable in the cubic lattice of arbitrary
Results 1  10
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20