Graphs with many hamiltonian paths

Sparse hamiltonian 2-decompositions together with exact count of numerous Hamilton cycles

Fuzzy Topographic Topological Mapping (FTTM) consists of four topological spaces that are homeomorphic to each other. A sequence of FTTMn is a combination of n terms of FTTM. An assembly graph is a graph with all vertices have valency of one or four. A Hamiltonian path is a path that visits every vertices of a graph exactly once. In this paper, we prove an assembly graphs exists in FTTMn and relation between the Hamiltonian polygonal paths and assembly graph of FTTMn. Several definitions and theorems are developed for the purpose.Fuzzy Topographic Topological Mapping (FTTM) consists of four topological spaces that are homeomorphic to each other. A sequence of FTTMn is a combination of n terms of FTTM. An assembly graph is a graph with all vertices have valency of one or four. A Hamiltonian path is a path that visits every vertices of a graph exactly once. In this paper, we prove an assembly graphs exists in FTTMn and relation between the Hamiltonian polygonal paths and assembly graph of FTTMn. Several definitions and theorems are developed for the purpose.

Hamiltonian cycles and paths in vertex-transitive graphs with abelian and nilpotent groups

On sparse hamiltonian 2-decompositions together with exact count of numerous Hamilton cycles

Many students are taught about genome assembly using the dichotomy between the complexity of finding Eulerian and Hamiltonian cycles (easy versus hard, respectively). This dichotomy is sometimes used to motivate the use of de Bruijn graphs in practice. In this paper, we explain that while de Bruijn graphs have indeed been very useful, the reason has nothing to do with the complexity of the Hamiltonian and Eulerian cycle problems. We give 2 arguments. The first is that a genome reconstruction is never unique and hence an algorithm for finding Eulerian or Hamiltonian cycles is not part of any assembly algorithm used in practice. The second is that even if an arbitrary genome reconstruction was desired, one could do so in linear time in both the Eulerian and Hamiltonian paradigms.

In this chapter, the concepts of Hamiltonian paths and Hamiltonian cycles are discussed. In the first section, the history of Hamiltonian graphs is described, and then some concepts such as Hamiltonian paths, Hamiltonian cycles, traceable graphs, and Hamiltonian graphs are defined. Also some most known Hamiltonian graph problems such as travelling salesman problem (TSP), Kirkman’s cell of a bee, Icosian game, and knight’s tour problem are presented. In addition, necessary and (or) sufficient conditions for existence of a Hamiltonian cycle are investigated. Furthermore, in order to solve Hamiltonian cycle problems, some algorithms are introduced in the last section.

Hamiltonian cycle and path embeddings in 3-ary [formula omitted]-cubes based on [formula omitted]-structure faults

A minimum Hamiltonian completion of a graph G is a minimum-size set of edges that, when added to G, guarantee a Hamiltonian path. Finding a Hamiltonian completion has applications to frequency assignment as well as distributed computing. If the new edges are deleted from the Hamiltonian path, one is left with a minimum path cover, a minimum-size set of vertex-disjoint paths that cover the vertices of G. For arbitrary graphs, constructing a minimum Hamiltonian completion or path cover is clearly NP-hard, but there exists a linear-time algorithm for trees. In this paper we first give a description and proof of correctness for this linear-time algorithm that is simpler and more intuitive than those given previously. We show that the algorithm extends also to unicyclic graphs. We then give a new method for finding an optimal path cover or Hamiltonian completion for a tree that uses a reduction to a maximum flow problem. In addition, we show how to extend the reduction to construct, if possible, a covering of the vertices of a bipartite graph with vertex-disjoint cycles, that is, a 2-factor.

A generated n-sequence of fuzzy topographic topological mapping, FTTM n , is a combination of n number of FTTM’s graphs. An assembly graph is a graph whereby its vertices have valency of one or four. A Hamiltonian path is a path that visits every vertex of the graph exactly once. In this paper, we prove that assembly graphs exist in FTTM n and establish their relations to the Hamiltonian polygonal paths. Finally, the relation between the Hamiltonian polygonal paths induced from FTTM n to the k-Fibonacci sequence is established and their upper and lower bounds’ number of paths is determined.

This paper studies techniques of finding hamiltonian paths and cycles in hypercubes and dense sets of hypercubes. This problem is, in general, easily solvable but here the problem was modified by the requirement that a set of edges has to be used in such path or cycle. The main result of this paper says that for a given n, any sufficiently large hypercube contains a hamiltonian path or cycle with prescribed n edges just when the family of the edges satisfies certain natural necessary conditions. Analogous results are presented for dense sets. © 2005 Wiley Periodicals, Inc. J Graph Theory

Dirac-type results for loose Hamilton cycles in uniform hypergraphs

Nash-Williams and Chvatal conditions (1969 and 1972) are well known and classical sufficient conditions for a graph to contain a Hamiltonian cycle. In this paper, we add constraints, called conflicts. A conflict is a pair of edges of the graph that cannot be both in a same Hamiltonian path or cycle. Given a graph G and a set of conflicts, we try to determine whether G contains such a Hamiltonian path or cycle without conflict. We focus in this paper on graphs in which each vertex is part of at most one conflict, called one-conflict graphs. We propose Nash-Williams-type and Chvatal-type results in this context.

Graph Theory For a positive integer n∈ℕ and a set D⊆ ℕ, the distance graph GnD has vertex set { 0,1,\textellipsis,n-1} and two vertices i and j of GnD are adjacent exactly if |j-i|∈D. The condition gcd(D)=1 is necessary for a distance graph GnD being connected. Let D={d1,d2}⊆ℕ be such that d1>d2 and gcd(d1,d2)=1. We prove the following results. If n is sufficiently large in terms of D, then GnD has a Hamiltonian path with endvertices 0 and n-1. If d1d2 is odd, n is even and sufficiently large in terms of D, then GnD has a Hamiltonian cycle. If d1d2 is even and n is sufficiently large in terms of D, then GnD has a Hamiltonian cycle.

This paper addresses the existence and construction of Hamiltonian paths and Hamiltonian cycles on conforming tetrahedral meshes. The paths and cycles are constrained to pass from one tetrahedron to the next one through a vertex. For conforming tetrahedral meshes, under certain conditions which are normally satisfied in finite-element computations, we show that there exists a through-vertex Hamiltonian path between any two tetrahedra. The proof is constructive from which an efficient algorithm for computing Hamiltonian paths and cycles can be directly derived.

Finding a Hamiltonian cycle in a graph is one of the classical NP-complete problems. Complexity of the Hamiltonian problem in permutation graphs has been a well-known open problem. In this paper the authors settle the complexity of the Hamiltonian problem in the more general class of cocomparability graphs. It is shown that the Hamiltonian cycle existence problem for cocomparability graphs is in P. A polynomial time algorithm for constructing a Hamiltonian path and cycle is also presented. The approach is based on exploiting the relationship between the Hamiltonian problem in a cocomparability graph and the bump number problem in a partial order corresponding to the transitive orientation of its complementary graph.