6 research outputs found
Solving Partition Problems Almost Always Requires Pushing Many Vertices Around
A fundamental graph problem is to recognize whether the vertex set of a graph G can be bipartitioned into sets A and B such that G[A] and G[B] satisfy properties Pi_A and Pi_B, respectively. This so-called (Pi_A,Pi_B)-Recognition problem generalizes amongst others the recognition of 3-colorable, bipartite, split, and monopolar graphs. A powerful algorithmic technique that can be used to obtain fixed-parameter algorithms for many cases of (Pi_A,Pi_B)-Recognition, as well as several other problems, is the pushing process. For bipartition problems, the process starts with an "almost correct" bipartition (A\u27,B\u27), and pushes appropriate vertices from A\u27 to B\u27 and vice versa to eventually arrive at a correct bipartition.
In this paper, we study whether (Pi_A,Pi_B)-Recognition problems for which the pushing process yields fixed-parameter algorithms also admit polynomial problem kernels. In our study, we focus on the first level above triviality, where Pi_A is the set of P_3-free graphs (disjoint unions of cliques, or cluster graphs), the parameter is the number of clusters in the cluster graph G[A], and Pi_B is characterized by a set H of connected forbidden induced subgraphs. We prove that, under the assumption that NP not subseteq coNP/poly, (Pi_A,Pi_B)-Recognition admits a polynomial kernel if and only if H contains a graph of order at most 2. In both the kernelization and the lower bound results, we make crucial use of the pushing process
Parameterized Algorithms on Perfect Graphs for deletion to -graphs
For fixed integers , a graph is called an {\em
-graph} if the vertex set can be partitioned into
independent sets and cliques. The class of graphs
generalizes -colourable graphs (when and hence not surprisingly,
determining whether a given graph is an -graph is \NP-hard even when
or in general graphs.
When and are part of the input, then the recognition problem is
NP-hard even if the input graph is a perfect graph (where the {\sc Chromatic
Number} problem is solvable in polynomial time). It is also known to be
fixed-parameter tractable (FPT) on perfect graphs when parameterized by and
. I.e. there is an f(r+\ell) \cdot n^{\Oh(1)} algorithm on perfect
graphs on vertices where is some (exponential) function of and
.
In this paper, we consider the parameterized complexity of the following
problem, which we call {\sc Vertex Partization}. Given a perfect graph and
positive integers decide whether there exists a set of size at most such that the deletion of from results in an
-graph. We obtain the following results: \begin{enumerate} \item {\sc
Vertex Partization} on perfect graphs is FPT when parameterized by .
\item The problem does not admit any polynomial sized kernel when parameterized
by . In other words, in polynomial time, the input graph can not be
compressed to an equivalent instance of size polynomial in . In fact,
our result holds even when .
\item When are universal constants, then {\sc Vertex Partization} on
perfect graphs, parameterized by , has a polynomial sized kernel.
\end{enumerate
Tight Kernels for Covering and Hitting: Point Hyperplane Cover and Polynomial Point Hitting Set
International audienceThe Point Hyperplane Cover problem in R d takes as input a set of n points in R d and a positive integer k. The objective is to cover all the given points with a set of at most k hyperplanes. The D-Polynomial Points Hitting Set (D-Polynomial Points HS) problem in R d takes as input a family F of D-degree polynomials from a vector space R in R d , and determines whether there is a set of at most k points in R d that hit all the polynomials in F. For both problems, we exhibit tight kernels where k is the parameter
Tight Kernels for Covering with Points and Polynomials
The Point Hyperplane Cover problem in takes as input a set of points in and a positive integer . The objective is to cover all the given points with a set of at most hyperplanes. The D-Polynomial Points Cover problem in takes as input a family of D-degree polynomials from a vector space in , and determines whether there is a set of at most points in that hit all the polynomials in . Here, a point p is said to hit a polynomial if . For both problems, we exhibit tight kernels where is the parameter. We also exhibit a tight kernel for the Projective Point Hyperplane Cover problem, where the hyperplanes that are allowed to cover the points must all contain a fixed point, and the fixed point cannot be included in the solution set of points