234 research outputs found
More Applications of the d-Neighbor Equivalence: Connectivity and Acyclicity Constraints
In this paper, we design a framework to obtain efficient algorithms for several problems with a global constraint (acyclicity or connectivity) such as Connected Dominating Set, Node Weighted Steiner Tree, Maximum Induced Tree, Longest Induced Path, and Feedback Vertex Set. For all these problems, we obtain 2^O(k)* n^O(1), 2^O(k log(k))* n^O(1), 2^O(k^2) * n^O(1) and n^O(k) time algorithms parameterized respectively by clique-width, Q-rank-width, rank-width and maximum induced matching width. Our approach simplifies and unifies the known algorithms for each of the parameters and match asymptotically also the running time of the best algorithms for basic NP-hard problems such as Vertex Cover and Dominating Set. Our framework is based on the d-neighbor equivalence defined in [Bui-Xuan, Telle and Vatshelle, TCS 2013]. The results we obtain highlight the importance and the generalizing power of this equivalence relation on width measures. We also prove that this equivalence relation could be useful for Max Cut: a W[1]-hard problem parameterized by clique-width. For this latter problem, we obtain n^O(k), n^O(k) and n^(2^O(k)) time algorithm parameterized by clique-width, Q-rank-width and rank-width
More applications of the d-neighbor equivalence: acyclicity and connectivity constraints
In this paper, we design a framework to obtain efficient algorithms for
several problems with a global constraint (acyclicity or connectivity) such as
Connected Dominating Set, Node Weighted Steiner Tree, Maximum Induced Tree,
Longest Induced Path, and Feedback Vertex Set. We design a meta-algorithm that
solves all these problems and whose running time is upper bounded by
, , and where is respectively the clique-width,
-rank-width, rank-width and maximum induced matching width of a
given decomposition. Our meta-algorithm simplifies and unifies the known
algorithms for each of the parameters and its running time matches
asymptotically also the running times of the best known algorithms for basic
NP-hard problems such as Vertex Cover and Dominating Set. Our framework is
based on the -neighbor equivalence defined in [Bui-Xuan, Telle and
Vatshelle, TCS 2013]. The results we obtain highlight the importance of this
equivalence relation on the algorithmic applications of width measures.
We also prove that our framework could be useful for -hard problems
parameterized by clique-width such as Max Cut and Maximum Minimal Cut. For
these latter problems, we obtain , and time
algorithms where is respectively the clique-width, the
-rank-width and the rank-width of the input graph
Parameterized Algorithms for Modular-Width
It is known that a number of natural graph problems which are FPT
parameterized by treewidth become W-hard when parameterized by clique-width. It
is therefore desirable to find a different structural graph parameter which is
as general as possible, covers dense graphs but does not incur such a heavy
algorithmic penalty.
The main contribution of this paper is to consider a parameter called
modular-width, defined using the well-known notion of modular decompositions.
Using a combination of ILPs and dynamic programming we manage to design FPT
algorithms for Coloring and Partitioning into paths (and hence Hamiltonian path
and Hamiltonian cycle), which are W-hard for both clique-width and its recently
introduced restriction, shrub-depth. We thus argue that modular-width occupies
a sweet spot as a graph parameter, generalizing several simpler notions on
dense graphs but still evading the "price of generality" paid by clique-width.Comment: to appear in IPEC 2013. arXiv admin note: text overlap with
arXiv:1304.5479 by other author
Subset feedback vertex set is fixed parameter tractable
The classical Feedback Vertex Set problem asks, for a given undirected graph
G and an integer k, to find a set of at most k vertices that hits all the
cycles in the graph G. Feedback Vertex Set has attracted a large amount of
research in the parameterized setting, and subsequent kernelization and
fixed-parameter algorithms have been a rich source of ideas in the field.
In this paper we consider a more general and difficult version of the
problem, named Subset Feedback Vertex Set (SUBSET-FVS in short) where an
instance comes additionally with a set S ? V of vertices, and we ask for a set
of at most k vertices that hits all simple cycles passing through S. Because of
its applications in circuit testing and genetic linkage analysis SUBSET-FVS was
studied from the approximation algorithms perspective by Even et al.
[SICOMP'00, SIDMA'00].
The question whether the SUBSET-FVS problem is fixed-parameter tractable was
posed independently by Kawarabayashi and Saurabh in 2009. We answer this
question affirmatively. We begin by showing that this problem is
fixed-parameter tractable when parametrized by |S|. Next we present an
algorithm which reduces the given instance to 2^k n^O(1) instances with the
size of S bounded by O(k^3), using kernelization techniques such as the
2-Expansion Lemma, Menger's theorem and Gallai's theorem. These two facts allow
us to give a 2^O(k log k) n^O(1) time algorithm solving the Subset Feedback
Vertex Set problem, proving that it is indeed fixed-parameter tractable.Comment: full version of a paper presented at ICALP'1
Grouped Domination Parameterized by Vertex Cover, Twin Cover, and Beyond
A dominating set of graph is called an -grouped dominating set if
can be partitioned into such that the size of each
unit is and the subgraph of induced by is connected. The
concept of -grouped dominating sets generalizes several well-studied
variants of dominating sets with requirements for connected component sizes,
such as the ordinary dominating sets (), paired dominating sets (),
and connected dominating sets ( is arbitrary and ). In this paper, we
investigate the computational complexity of -Grouped Dominating Set, which
is the problem of deciding whether a given graph has an -grouped dominating
set with at most units. For general , the problem is hard to solve in
various senses because the hardness of the connected dominating set is
inherited. We thus focus on the case in which is a constant or a parameter,
but we see that the problem for every fixed is still hard to solve. From
the hardness, we consider the parameterized complexity concerning well-studied
graph structural parameters. We first see that it is fixed-parameter tractable
for and treewidth, because the condition of -grouped domination for a
constant can be represented as monadic second-order logic (mso2). This is
good news, but the running time is not practical. We then design an
-time algorithm for general
, where is the twin cover number, which is a parameter between
vertex cover number and clique-width. For paired dominating set and trio
dominating set, i.e., , we can speed up the algorithm, whose
running time becomes . We further argue the relationship
between FPT results and graph parameters, which draws the parameterized
complexity landscape of -Grouped Dominating Set.Comment: 23 pages, 6 figure
Walking Through Waypoints
We initiate the study of a fundamental combinatorial problem: Given a
capacitated graph , find a shortest walk ("route") from a source to a destination that includes all vertices specified by a set
: the \emph{waypoints}. This waypoint routing problem
finds immediate applications in the context of modern networked distributed
systems. Our main contribution is an exact polynomial-time algorithm for graphs
of bounded treewidth. We also show that if the number of waypoints is
logarithmically bounded, exact polynomial-time algorithms exist even for
general graphs. Our two algorithms provide an almost complete characterization
of what can be solved exactly in polynomial-time: we show that more general
problems (e.g., on grid graphs of maximum degree 3, with slightly more
waypoints) are computationally intractable
Computing the Largest Bond of a Graph
A bond of a graph G is an inclusion-wise minimal disconnecting set of G, i.e., bonds are cut-sets that determine cuts [S,VS] of G such that G[S] and G[VS] are both connected. Given s,t in V(G), an st-bond of G is a bond whose removal disconnects s and t. Contrasting with the large number of studies related to maximum cuts, there are very few results regarding the largest bond of general graphs. In this paper, we aim to reduce this gap on the complexity of computing the largest bond and the largest st-bond of a graph. Although cuts and bonds are similar, we remark that computing the largest bond of a graph tends to be harder than computing its maximum cut. We show that Largest Bond remains NP-hard even for planar bipartite graphs, and it does not admit a constant-factor approximation algorithm, unless P = NP. We also show that Largest Bond and Largest st-Bond on graphs of clique-width w cannot be solved in time f(w) x n^{o(w)} unless the Exponential Time Hypothesis fails, but they can be solved in time f(w) x n^{O(w)}. In addition, we show that both problems are fixed-parameter tractable when parameterized by the size of the solution, but they do not admit polynomial kernels unless NP subseteq coNP/poly
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