42 research outputs found
Towards optimal kernel for connected vertex cover in planar graphs
We study the parameterized complexity of the connected version of the vertex
cover problem, where the solution set has to induce a connected subgraph.
Although this problem does not admit a polynomial kernel for general graphs
(unless NP is a subset of coNP/poly), for planar graphs Guo and Niedermeier
[ICALP'08] showed a kernel with at most 14k vertices, subsequently improved by
Wang et al. [MFCS'11] to 4k. The constant 4 here is so small that a natural
question arises: could it be already an optimal value for this problem? In this
paper we answer this quesion in negative: we show a (11/3)k-vertex kernel for
Connected Vertex Cover in planar graphs. We believe that this result will
motivate further study in search for an optimal kernel
Kernels for Feedback Arc Set In Tournaments
A tournament T=(V,A) is a directed graph in which there is exactly one arc
between every pair of distinct vertices. Given a digraph on n vertices and an
integer parameter k, the Feedback Arc Set problem asks whether the given
digraph has a set of k arcs whose removal results in an acyclic digraph. The
Feedback Arc Set problem restricted to tournaments is known as the k-Feedback
Arc Set in Tournaments (k-FAST) problem. In this paper we obtain a linear
vertex kernel for k-FAST. That is, we give a polynomial time algorithm which
given an input instance T to k-FAST obtains an equivalent instance T' on O(k)
vertices. In fact, given any fixed e>0, the kernelized instance has at most
(2+e)k vertices. Our result improves the previous known bound of O(k^2) on the
kernel size for k-FAST. Our kernelization algorithm solves the problem on a
subclass of tournaments in polynomial time and uses a known polynomial time
approximation scheme for k-FAST
Compression via Matroids: A Randomized Polynomial Kernel for Odd Cycle Transversal
The Odd Cycle Transversal problem (OCT) asks whether a given graph can be
made bipartite by deleting at most of its vertices. In a breakthrough
result Reed, Smith, and Vetta (Operations Research Letters, 2004) gave a
\BigOh(4^kkmn) time algorithm for it, the first algorithm with polynomial
runtime of uniform degree for every fixed . It is known that this implies a
polynomial-time compression algorithm that turns OCT instances into equivalent
instances of size at most \BigOh(4^k), a so-called kernelization. Since then
the existence of a polynomial kernel for OCT, i.e., a kernelization with size
bounded polynomially in , has turned into one of the main open questions in
the study of kernelization.
This work provides the first (randomized) polynomial kernelization for OCT.
We introduce a novel kernelization approach based on matroid theory, where we
encode all relevant information about a problem instance into a matroid with a
representation of size polynomial in . For OCT, the matroid is built to
allow us to simulate the computation of the iterative compression step of the
algorithm of Reed, Smith, and Vetta, applied (for only one round) to an
approximate odd cycle transversal which it is aiming to shrink to size . The
process is randomized with one-sided error exponentially small in , where
the result can contain false positives but no false negatives, and the size
guarantee is cubic in the size of the approximate solution. Combined with an
\BigOh(\sqrt{\log n})-approximation (Agarwal et al., STOC 2005), we get a
reduction of the instance to size \BigOh(k^{4.5}), implying a randomized
polynomial kernelization.Comment: Minor changes to agree with SODA 2012 version of the pape
Tight Kernel Bounds for Problems on Graphs with Small Degeneracy
In this paper we consider kernelization for problems on d-degenerate graphs,
i.e. graphs such that any subgraph contains a vertex of degree at most .
This graph class generalizes many classes of graphs for which effective
kernelization is known to exist, e.g. planar graphs, H-minor free graphs, and
H-topological-minor free graphs. We show that for several natural problems on
d-degenerate graphs the best known kernelization upper bounds are essentially
tight.Comment: Full version of ESA 201
On Polynomial Kernels for Integer Linear Programs: Covering, Packing and Feasibility
We study the existence of polynomial kernels for the problem of deciding
feasibility of integer linear programs (ILPs), and for finding good solutions
for covering and packing ILPs. Our main results are as follows: First, we show
that the ILP Feasibility problem admits no polynomial kernelization when
parameterized by both the number of variables and the number of constraints,
unless NP \subseteq coNP/poly. This extends to the restricted cases of bounded
variable degree and bounded number of variables per constraint, and to covering
and packing ILPs. Second, we give a polynomial kernelization for the Cover ILP
problem, asking for a solution to Ax >= b with c^Tx <= k, parameterized by k,
when A is row-sparse; this generalizes a known polynomial kernelization for the
special case with 0/1-variables and coefficients (d-Hitting Set)
Finding forest-orderings of tournaments is NP-complete
Given a class of (undirected) graphs , we say that a FAS is
a -FAS if the graph induced by the edges of (forgetting their
orientations) belongs to . We show that deciding if a tournament
has a -FAS is NP-complete when is the class of all
forests. We are motivated by connections between -FAS and
structural parameters of tournaments, such as the dichromatic number, the
clique number of tournaments, and the strong Erd\H{o}s-Hajnal property