33 research outputs found
Approximately coloring graphs without long induced paths
It is an open problem whether the 3-coloring problem can be solved in
polynomial time in the class of graphs that do not contain an induced path on
vertices, for fixed . We propose an algorithm that, given a 3-colorable
graph without an induced path on vertices, computes a coloring with
many colors. If the input graph is
triangle-free, we only need many
colors. The running time of our algorithm is if the input
graph has vertices and edges
Total coloring of 1-toroidal graphs of maximum degree at least 11 and no adjacent triangles
A {\em total coloring} of a graph is an assignment of colors to the
vertices and the edges of such that every pair of adjacent/incident
elements receive distinct colors. The {\em total chromatic number} of a graph
, denoted by \chiup''(G), is the minimum number of colors in a total
coloring of . The well-known Total Coloring Conjecture (TCC) says that every
graph with maximum degree admits a total coloring with at most colors. A graph is {\em -toroidal} if it can be drawn in torus such
that every edge crosses at most one other edge. In this paper, we investigate
the total coloring of -toroidal graphs, and prove that the TCC holds for the
-toroidal graphs with maximum degree at least~ and some restrictions on
the triangles. Consequently, if is a -toroidal graph with maximum degree
at least~ and without adjacent triangles, then admits a total
coloring with at most colors.Comment: 10 page
On Symbolic Ultrametrics, Cotree Representations, and Cograph Edge Decompositions and Partitions
Symbolic ultrametrics define edge-colored complete graphs K_n and yield a
simple tree representation of K_n. We discuss, under which conditions this idea
can be generalized to find a symbolic ultrametric that, in addition,
distinguishes between edges and non-edges of arbitrary graphs G=(V,E) and thus,
yielding a simple tree representation of G. We prove that such a symbolic
ultrametric can only be defined for G if and only if G is a so-called cograph.
A cograph is uniquely determined by a so-called cotree. As not all graphs are
cographs, we ask, furthermore, what is the minimum number of cotrees needed to
represent the topology of G. The latter problem is equivalent to find an
optimal cograph edge k-decomposition {E_1,...,E_k} of E so that each subgraph
(V,E_i) of G is a cograph. An upper bound for the integer k is derived and it
is shown that determining whether a graph has a cograph 2-decomposition, resp.,
2-partition is NP-complete
Parameterized Complexity of Maximum Edge Colorable Subgraph
A graph is {\em -edge colorable} if there is a coloring , such that for distinct , we have
. The {\sc Maximum Edge-Colorable Subgraph} problem
takes as input a graph and integers and , and the objective is to
find a subgraph of and a -edge-coloring of , such that . We study the above problem from the viewpoint of Parameterized
Complexity. We obtain \FPT\ algorithms when parameterized by: the vertex
cover number of , by using {\sc Integer Linear Programming}, and ,
a randomized algorithm via a reduction to \textsc{Rainbow Matching}, and a
deterministic algorithm by using color coding, and divide and color. With
respect to the parameters , where is one of the following: the
solution size, , the vertex cover number of , and l -
{\mm}(G), where {\mm}(G) is the size of a maximum matching in ; we show
that the (decision version of the) problem admits a kernel with vertices. Furthermore, we show that there is no kernel of size
, for any and computable
function , unless \NP \subseteq \CONPpoly
Machine speed scaling by adapting methods for convex optimization with submodular constraints
In this paper, we propose a new methodology for the speed-scaling problem based on its link to scheduling with controllable processing times and submodular optimization. It results in faster algorithms for traditional speed-scaling models, characterized by a common speed/energy function. Additionally, it efficiently handles the most general models with job-dependent speed/energy functions with single and multiple machines. To the best of our knowledge, this has not been addressed prior to this study. In particular, the general version of the single-machine case is solvable by the new technique in O(n2) time
The complexity of counting edge colorings and a dichotomy for some higher domain Holant problems
We show that an effective version of Siegel’s Theorem on finiteness of integer solutions and an application of elementary Galois theory are key ingredients in a complexity classification of some Holant problems. These Holant problems, denoted by Holant(f), are defined by a symmetric ternary function f that is invariant under any permutation of the κ ≥ 3 domain elements. We prove that Holant(f) exhibits a complexity dichotomy. This dichotomy holds even when restricted to planar graphs. A special case of this result is that counting edge κ-colorings is #P-hard over planar 3-regular graphs for κ ≥ 3. In fact, we prove that counting edge κ-colorings is #P-hard over planar r-regular graphs for all κ ≥ r ≥ 3. The problem is polynomial-time computable in all other parameter settings. The proof of the dichotomy theorem for Holant(f) depends on the fact that a specific polynomial p(x, y) has an explicitly listed finite set of integer solutions, and the determination of the Galois groups of some specific polynomials. In the process, we also encounter the Tutte polynomial, medial graphs, Eulerian partitions, Puiseux series, and a certain lattice condition on the (logarithm of) the roots of polynomials.