9,835 research outputs found
On the Parameterized Complexity of Computing st-Orientations with Few Transitive Edges
Orienting the edges of an undirected graph such that the resulting digraph satisfies some given constraints is a classical problem in graph theory, with multiple algorithmic applications. In particular, an st-orientation orients each edge of the input graph such that the resulting digraph is acyclic, and it contains a single source s and a single sink t. Computing an st-orientation of a graph can be done efficiently, and it finds notable applications in graph algorithms and in particular in graph drawing. On the other hand, finding an st-orientation with at most k transitive edges is more challenging and it was recently proven to be NP-hard already when k = 0. We strengthen this result by showing that the problem remains NP-hard even for graphs of bounded diameter, and for graphs of bounded vertex degree. These computational lower bounds naturally raise the question about which structural parameters can lead to tractable parameterizations of the problem. Our main result is a fixed-parameter tractable algorithm parameterized by treewidth
On the Parameterized Complexity of Computing -Orientations with Few Transitive Edges
Orienting the edges of an undirected graph such that the resulting digraph
satisfies some given constraints is a classical problem in graph theory, with
multiple algorithmic applications. In particular, an -orientation orients
each edge of the input graph such that the resulting digraph is acyclic, and it
contains a single source and a single sink . Computing an
-orientation of a graph can be done efficiently, and it finds notable
applications in graph algorithms and in particular in graph drawing. On the
other hand, finding an -orientation with at most transitive edges is
more challenging and it was recently proven to be NP-hard already when .
We strengthen this result by showing that the problem remains NP-hard even for
graphs of bounded diameter, and for graphs of bounded vertex degree. These
computational lower bounds naturally raise the question about which structural
parameters can lead to tractable parameterizations of the problem. Our main
result is a fixed-parameter tractable algorithm parameterized by treewidth
The Complexity of Finding Effectors
The NP-hard EFFECTORS problem on directed graphs is motivated by applications
in network mining, particularly concerning the analysis of probabilistic
information-propagation processes in social networks. In the corresponding
model the arcs carry probabilities and there is a probabilistic diffusion
process activating nodes by neighboring activated nodes with probabilities as
specified by the arcs. The point is to explain a given network activation state
as well as possible by using a minimum number of "effector nodes"; these are
selected before the activation process starts.
We correct, complement, and extend previous work from the data mining
community by a more thorough computational complexity analysis of EFFECTORS,
identifying both tractable and intractable cases. To this end, we also exploit
a parameterization measuring the "degree of randomness" (the number of "really"
probabilistic arcs) which might prove useful for analyzing other probabilistic
network diffusion problems as well.Comment: 28 page
On the Computational Complexity of Vertex Integrity and Component Order Connectivity
The Weighted Vertex Integrity (wVI) problem takes as input an -vertex
graph , a weight function , and an integer . The
task is to decide if there exists a set such that the weight
of plus the weight of a heaviest component of is at most . Among
other results, we prove that:
(1) wVI is NP-complete on co-comparability graphs, even if each vertex has
weight ;
(2) wVI can be solved in time;
(3) wVI admits a kernel with at most vertices.
Result (1) refutes a conjecture by Ray and Deogun and answers an open
question by Ray et al. It also complements a result by Kratsch et al., stating
that the unweighted version of the problem can be solved in polynomial time on
co-comparability graphs of bounded dimension, provided that an intersection
model of the input graph is given as part of the input.
An instance of the Weighted Component Order Connectivity (wCOC) problem
consists of an -vertex graph , a weight function ,
and two integers and , and the task is to decide if there exists a set
such that the weight of is at most and the weight of
a heaviest component of is at most . In some sense, the wCOC problem
can be seen as a refined version of the wVI problem. We prove, among other
results, that:
(4) wCOC can be solved in time on interval graphs,
while the unweighted version can be solved in time on this graph
class;
(5) wCOC is W[1]-hard on split graphs when parameterized by or by ;
(6) wCOC can be solved in time;
(7) wCOC admits a kernel with at most vertices.
We also show that result (6) is essentially tight by proving that wCOC cannot
be solved in time, unless the ETH fails.Comment: A preliminary version of this paper already appeared in the
conference proceedings of ISAAC 201
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