6 research outputs found
Parameterized Algorithms for Min-Max Multiway Cut and List Digraph Homomorphism
In this paper we design {\sf FPT}-algorithms for two parameterized problems.
The first is \textsc{List Digraph Homomorphism}: given two digraphs and
and a list of allowed vertices of for every vertex of , the question is
whether there exists a homomorphism from to respecting the list
constraints. The second problem is a variant of \textsc{Multiway Cut}, namely
\textsc{Min-Max Multiway Cut}: given a graph , a non-negative integer
, and a set of terminals, the question is whether we can
partition the vertices of into parts such that (a) each part contains
one terminal and (b) there are at most edges with only one endpoint in
this part. We parameterize \textsc{List Digraph Homomorphism} by the number
of edges of that are mapped to non-loop edges of and we give a time
algorithm, where is the order of the host graph . We also prove that
\textsc{Min-Max Multiway Cut} can be solved in time . Our approach introduces a general problem, called
{\sc List Allocation}, whose expressive power permits the design of
parameterized reductions of both aforementioned problems to it. Then our
results are based on an {\sf FPT}-algorithm for the {\sc List Allocation}
problem that is designed using a suitable adaptation of the {\em randomized
contractions} technique (introduced by [Chitnis, Cygan, Hajiaghayi, Pilipczuk,
and Pilipczuk, FOCS 2012]).Comment: An extended abstract of this work will appear in the Proceedings of
the 10th International Symposium on Parameterized and Exact Computation
(IPEC), Patras, Greece, September 201
On the complexity of computing the -restricted edge-connectivity of a graph
The \emph{-restricted edge-connectivity} of a graph , denoted by
, is defined as the minimum size of an edge set whose removal
leaves exactly two connected components each containing at least vertices.
This graph invariant, which can be seen as a generalization of a minimum
edge-cut, has been extensively studied from a combinatorial point of view.
However, very little is known about the complexity of computing .
Very recently, in the parameterized complexity community the notion of
\emph{good edge separation} of a graph has been defined, which happens to be
essentially the same as the -restricted edge-connectivity. Motivated by the
relevance of this invariant from both combinatorial and algorithmic points of
view, in this article we initiate a systematic study of its computational
complexity, with special emphasis on its parameterized complexity for several
choices of the parameters. We provide a number of NP-hardness and W[1]-hardness
results, as well as FPT-algorithms.Comment: 16 pages, 4 figure
Parameterized algorithms for min-max multiway cut and list digraph homomorphism
We design FPT-algorithms for the following problems. The first is LIST DIGRAPH HOMOMORPHISM: given two digraphs G and H, with order n and h, respectively, and a list of allowed vertices of H for every vertex of G, does there exist a homomorphism from G to H respecting the list constraints? Let â be the number of edges of G mapped to non-loop edges of H. The second problem is MIN-MAX MULTIWAY CUT: given a graph G, an integer ââ„0, and a set T of r terminals, can we partition V(G) into r parts such that each part contains one terminal and there are at most â edges with only one endpoint in this part? We solve both problems in time 2O(ââ
logâĄh+â2â
logâĄâ)â
n4â
logâĄn and 2O((âr)2logâĄâr)â
n4â
logâĄn, respectively, via a reduction to a new problem called LIST ALLOCATION, which we solve adapting the randomized contractions technique of Chitnis et al. (2012) [4]. © 2017 Elsevier Inc
Parameterized algorithms for min-max multiway cut and list digraph homomorphism
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