40 research outputs found
Note on 3-Coloring of -Free Graphs
We show that the 3-coloring problem is polynomial-time solvable on
-free graphs.Comment: 17 pages, 13 figure
-Critical Graphs in -Free Graphs
Given two graphs and , a graph is -free if it
contains no induced subgraph isomorphic to or . Let be the
path on vertices. A graph is -vertex-critical if has chromatic
number but every proper induced subgraph of has chromatic number less
than . The study of -vertex-critical graphs for graph classes is an
important topic in algorithmic graph theory because if the number of such
graphs that are in a given hereditary graph class is finite, then there is a
polynomial-time algorithm to decide if a graph in the class is
-colorable.
In this paper, we initiate a systematic study of the finiteness of
-vertex-critical graphs in subclasses of -free graphs. Our main result
is a complete classification of the finiteness of -vertex-critical graphs in
the class of -free graphs for all graphs on 4 vertices. To obtain
the complete dichotomy, we prove the finiteness for four new graphs using
various techniques -- such as Ramsey-type arguments and the dual of Dilworth's
Theorem -- that may be of independent interest.Comment: 18 page
Open problems on graph coloring for special graph classes.
For a given graph G and integer k, the Coloring problem is that of testing whether G has a k-coloring, that is, whether there exists a vertex mapping c:V→{1,2,…}c:V→{1,2,…} such that c(u)≠c(v)c(u)≠c(v) for every edge uv∈Euv∈E. We survey known results on the computational complexity of Coloring for graph classes that are hereditary or for which some graph parameter is bounded. We also consider coloring variants, such as precoloring extensions and list colorings and give some open problems in the area of on-line coloring
Graphs of Edge-Intersecting Non-Splitting Paths in a Tree: Representations of Holes-Part II
Given a tree and a set P of non-trivial simple paths on it, VPT(P) is the VPT
graph (i.e. the vertex intersection graph) of the paths P, and EPT(P) is the
EPT graph (i.e. the edge intersection graph) of P. These graphs have been
extensively studied in the literature. Given two (edge) intersecting paths in a
graph, their split vertices is the set of vertices having degree at least 3 in
their union. A pair of (edge) intersecting paths is termed non-splitting if
they do not have split vertices (namely if their union is a path). We define
the graph ENPT(P) of edge intersecting non-splitting paths of a tree, termed
the ENPT graph, as the graph having a vertex for each path in P, and an edge
between every pair of vertices representing two paths that are both
edge-intersecting and non-splitting. A graph G is an ENPT graph if there is a
tree T and a set of paths P of T such that G=ENPT(P), and we say that is
a representation of G.
Our goal is to characterize the representation of chordless ENPT cycles
(holes). To achieve this goal, we first assume that the EPT graph induced by
the vertices of an ENPT hole is given. In [2] we introduce three assumptions
(P1), (P2), (P3) defined on EPT, ENPT pairs of graphs. In the same study, we
define two problems HamiltonianPairRec, P3-HamiltonianPairRec and characterize
the representations of ENPT holes that satisfy (P1), (P2), (P3).
In this work, we continue our work by relaxing these three assumptions one by
one. We characterize the representations of ENPT holes satisfying (P3) by
providing a polynomial-time algorithm to solve P3-HamiltonianPairRec. We also
show that there does not exist a polynomial-time algorithm to solve
HamiltonianPairRec, unless P=NP
Structure and coloring of (, , diamond)-free graphs
We use and to denote a path and a cycle on t vertices,
respectively. A diamond consists of two triangles that share exactly one edge,
a kite is a graph obtained from a diamond by adding a new vertex adjacent to a
vertex of degree 2 of the diamond, a paraglider is the graph that consists of a
plus a vertex adjacent to three vertices of the , a paw is a graph
obtained from a triangle by adding a pendant edge. A comparable pair
consists of two nonadjacent vertices and such that
or . A universal clique is a clique such that for any two vertices and . A blowup of a
graph H is a graph obtained by substituting a stable set for each vertex, and
correspondingly replacing each edge by a complete bipartite graph. We prove
that 1) there is a unique connected imperfect , kite,
paraglider)-free graph G with \delta(G) \geq \omega(G)+ 1 which has no clique
cutsets, no comparable pairs, and no universal cliques; 2) if G is a connected
imperfect , diamond)-free graph with \delta(G) \geq max{3,
\omega(G)} and without comparable pairs, then G is isomorphic to a graph of a
well defined 12 graph families; and 3) each connected imperfect ,
paw)-free graph is a blowup of . As consequences, we show that \chi(G)
\leq \omega(G)+1 if G is (P7, C5, kite, paraglider)-free, and \chi(G) \leq
max{3, \omega(G)} if G is , H)-free with H being a diamond or a paw.
We also show that \chi(G) \le
Exploiting structure to cope with NP-hard graph problems: Polynomial and exponential time exact algorithms
An ideal algorithm for solving a particular problem always finds an optimal solution, finds such a solution for every possible instance, and finds it in polynomial time. When dealing with NP-hard problems, algorithms can only be expected to possess at most two out of these three desirable properties. All algorithms presented in this thesis are exact algorithms, which means that they always find an optimal solution. Demanding the solution to be optimal means that other concessions have to be made when designing an exact algorithm for an NP-hard problem: we either have to impose restrictions on the instances of the problem in order to achieve a polynomial time complexity, or we have to abandon the requirement that the worst-case running time has to be polynomial. In some cases, when the problem under consideration remains NP-hard on restricted input, we are even forced to do both.
Most of the problems studied in this thesis deal with partitioning the vertex set of a given graph. In the other problems the task is to find certain types of paths and cycles in graphs. The problems all have in common that they are NP-hard on general graphs. We present several polynomial time algorithms for solving restrictions of these problems to specific graph classes, in particular graphs without long induced paths, chordal graphs and claw-free graphs. For problems that remain NP-hard even on restricted input we present exact exponential time algorithms. In the design of each of our algorithms, structural graph properties have been heavily exploited. Apart from using existing structural results, we prove new structural properties of certain types of graphs in order to obtain our algorithmic results
Boundary properties of graphs
A set of graphs may acquire various desirable properties, if we apply suitable restrictions
on the set. We investigate the following two questions: How far, exactly, must one restrict
the structure of a graph to obtain a certain interesting property? What kind of tools are
helpful to classify sets of graphs into those which satisfy a property and those that do not?
Equipped with a containment relation, a graph class is a special example of a partially
ordered set. We introduce the notion of a boundary ideal as a generalisation of a notion
introduced by Alekseev in 2003, to provide a tool to indicate whether a partially ordered set
satisfies a desirable property or not. This tool can give a complete characterisation of lower
ideals defined by a finite forbidden set, into those that satisfy the given property and to
those that do not. In the case of graphs, a lower ideal with respect to the induced subgraph
relation is known as a hereditary graph class.
We study three interrelated types of properties for hereditary graph classes: the existence
of an efficient solution to an algorithmic graph problem, the boundedness of the graph
parameter known as clique-width, and well-quasi-orderability by the induced subgraph relation.
It was shown by Courcelle, Makowsky and Rotics in 2000 that, for a graph class, boundedness
of clique-width immediately implies an efficient solution to a wide range of algorithmic
problems. This serves as one of the motivations to study clique-width. As for well-quasiorderability,
we conjecture that every hereditary graph class that is well-quasi-ordered by
the induced subgraph relation also has bounded clique-width.
We discover the first boundary classes for several algorithmic graph problems, including
the Hamiltonian cycle problem. We also give polynomial-time algorithms for the dominating
induced matching problem, for some restricted graph classes.
After discussing the special importance of bipartite graphs in the study of clique-width,
we describe a general framework for constructing bipartite graphs of large clique-width. As
a consequence, we find a new minimal class of unbounded clique-width.
We prove numerous positive and negative results regarding the well-quasi-orderability of
classes of bipartite graphs. This completes a characterisation of the well-quasi-orderability of
all classes of bipartite graphs defined by one forbidden induced bipartite subgraph. We also
make considerable progress in characterising general graph classes defined by two forbidden
induced subgraphs, reducing the task to a small finite number of open cases. Finally, we
show that, in general, for hereditary graph classes defined by a forbidden set of bounded
finite size, a similar reduction is not usually possible, but the number of boundary classes
to determine well-quasi-orderability is nevertheless finite.
Our results, together with the notion of boundary ideals, are also relevant for the study
of other partially ordered sets in mathematics, such as permutations ordered by the pattern
containment relation