98 research outputs found
Paradigms for Parameterized Enumeration
The aim of the paper is to examine the computational complexity and
algorithmics of enumeration, the task to output all solutions of a given
problem, from the point of view of parameterized complexity. First we define
formally different notions of efficient enumeration in the context of
parameterized complexity. Second we show how different algorithmic paradigms
can be used in order to get parameter-efficient enumeration algorithms in a
number of examples. These paradigms use well-known principles from the design
of parameterized decision as well as enumeration techniques, like for instance
kernelization and self-reducibility. The concept of kernelization, in
particular, leads to a characterization of fixed-parameter tractable
enumeration problems.Comment: Accepted for MFCS 2013; long version of the pape
Letter graphs and geometric grid classes of permutations: characterization and recognition
In this paper, we reveal an intriguing relationship between two seemingly
unrelated notions: letter graphs and geometric grid classes of permutations. An
important property common for both of them is well-quasi-orderability,
implying, in a non-constructive way, a polynomial-time recognition of geometric
grid classes of permutations and -letter graphs for a fixed . However,
constructive algorithms are available only for . In this paper, we present
the first constructive polynomial-time algorithm for the recognition of
-letter graphs. It is based on a structural characterization of graphs in
this class.Comment: arXiv admin note: text overlap with arXiv:1108.6319 by other author
Partial Covering Arrays: Algorithms and Asymptotics
A covering array is an array with entries
in , for which every subarray contains each
-tuple of among its rows. Covering arrays find
application in interaction testing, including software and hardware testing,
advanced materials development, and biological systems. A central question is
to determine or bound , the minimum number of rows of
a . The well known bound
is not too far from being
asymptotically optimal. Sensible relaxations of the covering requirement arise
when (1) the set need only be contained among the rows
of at least of the subarrays and (2) the
rows of every subarray need only contain a (large) subset of . In this paper, using probabilistic methods, significant
improvements on the covering array upper bound are established for both
relaxations, and for the conjunction of the two. In each case, a randomized
algorithm constructs such arrays in expected polynomial time
Fast branching algorithm for Cluster Vertex Deletion
In the family of clustering problems, we are given a set of objects (vertices
of the graph), together with some observed pairwise similarities (edges). The
goal is to identify clusters of similar objects by slightly modifying the graph
to obtain a cluster graph (disjoint union of cliques). Hueffner et al. [Theory
Comput. Syst. 2010] initiated the parameterized study of Cluster Vertex
Deletion, where the allowed modification is vertex deletion, and presented an
elegant O(2^k * k^9 + n * m)-time fixed-parameter algorithm, parameterized by
the solution size. In our work, we pick up this line of research and present an
O(1.9102^k * (n + m))-time branching algorithm
Partitioning a graph into disjoint cliques and a triangle-free graph
A graph G=(V,E) is partitionable if there exists a partition {A,B} of V such that A induces a disjoint union of cliques (i.e., G[A] is P_3-free) and B induces a triangle-free graph (i.e., G[B] is K_3-free). In this paper we investigate the computational complexity of deciding whether a graph is partitionable. The problem is known to be NP-complete on arbitrary graphs. Here it is proved that if a graph G is bull-free, planar, perfect, K_4-free or does not contain certain holes then deciding whether G is partitionable is NP-complete. This answers an open question posed by Thomassé, Trotignon and Vušković. In contrast a finite list of forbidden induced subgraphs is given for partitionable cographs
Well-quasi-ordering versus clique-width : new results on bigenic classes.
Daligault, Rao and Thomassé conjectured that if a hereditary class of graphs is well-quasi-ordered by the induced subgraph relation then it has bounded clique-width. Lozin, Razgon and Zamaraev recently showed that this conjecture is not true for infinitely defined classes. For finitely defined classes the conjecture is still open. It is known to hold for classes of graphs defined by a single forbidden induced subgraph H, as such graphs are well-quasi-ordered and are of bounded clique-width if and only if H is an induced subgraph of P4P4. For bigenic classes of graphs i.e. ones defined by two forbidden induced subgraphs there are several open cases in both classifications. We reduce the number of open cases for well-quasi-orderability of such classes from 12 to 9. Our results agree with the conjecture and imply that there are only two remaining cases to verify for bigenic classes
A Counterexample Regarding Labelled Well-Quasi-Ordering
Korpelainen, Lozin, and Razgon conjectured that a hereditary property of graphs which is well-quasi-ordered by the induced subgraph order and defined by only finitely many minimal forbidden induced subgraphs is labelled well-quasi-ordered, a notion stronger than that of n-well-quasi-order introduced by Pouzet in the 1970s. We present a counterexample to this conjecture. In fact, we exhibit a hereditary property of graphs which is well-quasi-ordered by the induced subgraph order and defined by finitely many minimal forbidden induced subgraphs yet is not 2-well-quasi-ordered. This counterexample is based on the widdershins spiral, which has received some study in the area of permutation patterns
Towards Optimal and Expressive Kernelization for d-Hitting Set
d-Hitting Set is the NP-hard problem of selecting at most k vertices of a
hypergraph so that each hyperedge, all of which have cardinality at most d,
contains at least one selected vertex. The applications of d-Hitting Set are,
for example, fault diagnosis, automatic program verification, and the
noise-minimizing assignment of frequencies to radio transmitters.
We show a linear-time algorithm that transforms an instance of d-Hitting Set
into an equivalent instance comprising at most O(k^d) hyperedges and vertices.
In terms of parameterized complexity, this is a problem kernel. Our
kernelization algorithm is based on speeding up the well-known approach of
finding and shrinking sunflowers in hypergraphs, which yields problem kernels
with structural properties that we condense into the concept of expressive
kernelization.
We conduct experiments to show that our kernelization algorithm can kernelize
instances with more than 10^7 hyperedges in less than five minutes.
Finally, we show that the number of vertices in the problem kernel can be
further reduced to O(k^{d-1}) with additional O(k^{1.5 d}) processing time by
nontrivially combining the sunflower technique with d-Hitting Set problem
kernels due to Abu-Khzam and Moser.Comment: This version gives corrected experimental results, adds additional
figures, and more formally defines "expressive kernelization
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