397 research outputs found
Tractable classes of binary CSPs defined by excluded topological minors
The binary Constraint Satisfaction Problem (CSP) is to decide whether there exists an assignment to a set of variables which satisfies specified constraints between pairs of variables. A CSP instance can be presented as a labelled graph (called the microstructure) encoding both the forms of the constraints and where they are imposed. We consider subproblems defined by restricting the allowed form of the microstructure. One form of restriction that has previously been considered is to forbid certain specified substructures (patterns). This captures some tractable classes of the CSP, but does not capture the well-known property of acyclicity. In this paper we introduce the notion of a topological minor of a binary CSP instance. By forbidding certain patterns as topological minors we obtain a compact mechanism for expressing several novel tractable classes, including new generalisations of the class of acyclic instances
On Brambles, Grid-Like Minors, and Parameterized Intractability of Monadic Second-Order Logic
Brambles were introduced as the dual notion to treewidth, one of the most
central concepts of the graph minor theory of Robertson and Seymour. Recently,
Grohe and Marx showed that there are graphs G, in which every bramble of order
larger than the square root of the treewidth is of exponential size in |G|. On
the positive side, they show the existence of polynomial-sized brambles of the
order of the square root of the treewidth, up to log factors. We provide the
first polynomial time algorithm to construct a bramble in general graphs and
achieve this bound, up to log-factors. We use this algorithm to construct
grid-like minors, a replacement structure for grid-minors recently introduced
by Reed and Wood, in polynomial time. Using the grid-like minors, we introduce
the notion of a perfect bramble and an algorithm to find one in polynomial
time. Perfect brambles are brambles with a particularly simple structure and
they also provide us with a subgraph that has bounded degree and still large
treewidth; we use them to obtain a meta-theorem on deciding certain
parameterized subgraph-closed problems on general graphs in time singly
exponential in the parameter.
The second part of our work deals with providing a lower bound to Courcelle's
famous theorem, stating that every graph property that can be expressed by a
sentence in monadic second-order logic (MSO), can be decided by a linear time
algorithm on classes of graphs of bounded treewidth. Using our results from the
first part of our work we establish a strong lower bound for tractability of
MSO on classes of colored graphs
Hitting forbidden minors: Approximation and Kernelization
We study a general class of problems called F-deletion problems. In an
F-deletion problem, we are asked whether a subset of at most vertices can
be deleted from a graph such that the resulting graph does not contain as a
minor any graph from the family F of forbidden minors.
We obtain a number of algorithmic results on the F-deletion problem when F
contains a planar graph. We give (1) a linear vertex kernel on graphs excluding
-claw , the star with leves, as an induced subgraph, where
is a fixed integer. (2) an approximation algorithm achieving an approximation
ratio of , where is the size of an optimal solution on
general undirected graphs. Finally, we obtain polynomial kernels for the case
when F contains graph as a minor for a fixed integer . The graph
consists of two vertices connected by parallel edges. Even
though this may appear to be a very restricted class of problems it already
encompasses well-studied problems such as {\sc Vertex Cover}, {\sc Feedback
Vertex Set} and Diamond Hitting Set. The generic kernelization algorithm is
based on a non-trivial application of protrusion techniques, previously used
only for problems on topological graph classes
Finding detours is fixed-parameter tractable
We consider the following natural "above guarantee" parameterization of the
classical Longest Path problem: For given vertices s and t of a graph G, and an
integer k, the problem Longest Detour asks for an (s,t)-path in G that is at
least k longer than a shortest (s,t)-path. Using insights into structural graph
theory, we prove that Longest Detour is fixed-parameter tractable (FPT) on
undirected graphs and actually even admits a single-exponential algorithm, that
is, one of running time exp(O(k)) poly(n). This matches (up to the base of the
exponential) the best algorithms for finding a path of length at least k.
Furthermore, we study the related problem Exact Detour that asks whether a
graph G contains an (s,t)-path that is exactly k longer than a shortest
(s,t)-path. For this problem, we obtain a randomized algorithm with running
time about 2.746^k, and a deterministic algorithm with running time about
6.745^k, showing that this problem is FPT as well. Our algorithms for Exact
Detour apply to both undirected and directed graphs.Comment: Extended abstract appears at ICALP 201
Smooth Approximations and Relational Width Collapses
We prove that relational structures admitting specific polymorphisms (namely,
canonical pseudo-WNU operations of all arities ) have low relational
width. This implies a collapse of the bounded width hierarchy for numerous
classes of infinite-domain CSPs studied in the literature. Moreover, we obtain
a characterization of bounded width for first-order reducts of unary structures
and a characterization of MMSNP sentences that are equivalent to a Datalog
program, answering a question posed by Bienvenu, ten Cate, Lutz, and Wolter. In
particular, the bounded width hierarchy collapses in those cases as well
Tree Diet: Reducing the Treewidth to Unlock FPT Algorithms in RNA Bioinformatics
Hard graph problems are ubiquitous in Bioinformatics, inspiring the design of specialized Fixed-Parameter Tractable algorithms, many of which rely on a combination of tree-decomposition and dynamic programming. The time/space complexities of such approaches hinge critically on low values for the treewidth tw of the input graph. In order to extend their scope of applicability, we introduce the Tree-Diet problem, i.e. the removal of a minimal set of edges such that a given tree-decomposition can be slimmed down to a prescribed treewidth tw\u27. Our rationale is that the time gained thanks to a smaller treewidth in a parameterized algorithm compensates the extra post-processing needed to take deleted edges into account.
Our core result is an FPT dynamic programming algorithm for Tree-Diet, using 2^{O(tw)}n time and space. We complement this result with parameterized complexity lower-bounds for stronger variants (e.g., NP-hardness when tw\u27 or tw-tw\u27 is constant). We propose a prototype implementation for our approach which we apply on difficult instances of selected RNA-based problems: RNA design, sequence-structure alignment, and search of pseudoknotted RNAs in genomes, revealing very encouraging results. This work paves the way for a wider adoption of tree-decomposition-based algorithms in Bioinformatics
When the decomposition meets the constraint satisfaction problem
This paper explores the joint use of decomposition methods and parallel computing for solving constraint satisfaction problems and introduces a framework called Parallel Decomposition for Constraint Satisfaction Problems (PD-CSP). The main idea is that the set of constraints are first clustered using a decomposition algorithm in which highly correlated constraints are grouped together. Next, parallel search of variables is performed on the produced clusters in a way that is friendly for parallel computing. In particular, for the first step, we propose the adaptation of two well-known clustering algorithms ( k -means and DBSCAN). For the second step, we develop a GPU-based approach to efficiently explore the clusters. The results from the extensive experimental evaluation show that the PD-CSP provides competitive results in terms of accuracy and runtime
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