131 research outputs found
On Spanning Galaxies in Digraphs
International audienceIn a directed graph, a star is an arborescence with at least one arc, in which the root dominates all the other vertices. A galaxy is a vertex-disjoint union of stars. In this paper, we consider the Spanning Galaxy problem of deciding whether a digraph D has a spanning galaxy or not. We show that although this problem is NP-complete (even when restricted to acyclic digraphs), it becomes polynomial-time solvable when restricted to strong digraphs. In fact, we prove that restricted to this class, the \pb\ is equivalent to the problem of deciding if a strong digraph has a strong digraph with an even number of vertices. We then show a polynomial-time algorithm to solve this problem. We also consider some parameterized version of the Spanning Galaxy problem. Finally, we improve some results concerning the notion of directed star arboricity of a digraph D, which is the minimum number of galaxies needed to cover all the arcs of D. We show in particular that dst(D)\leq \Delta(D)+1 for every digraph D and that dst(D)\leq\Delta(D) for every acyclic digraph D
Precedence-Constrained Arborescences
The minimum-cost arborescence problem is a well-studied problem in the area
of graph theory, with known polynomial-time algorithms for solving it. Previous
literature introduced new variations on the original problem with different
objective function and/or constraints. Recently, the Precedence-Constrained
Minimum-Cost Arborescence problem was proposed, in which precedence constraints
are enforced on pairs of vertices. These constraints prevent the formation of
directed paths that violate precedence relationships along the tree. We show
that this problem is NP-hard, and we introduce a new scalable mixed integer
linear programming model for it. With respect to the previous models, the newly
proposed model performs substantially better. This work also introduces a new
variation on the minimum-cost arborescence problem with precedence constraints.
We show that this new variation is also NP-hard, and we propose several mixed
integer linear programming models for formulating the problem
Approximation Algorithms for Flexible Graph Connectivity
We present approximation algorithms for several network design problems in
the model of Flexible Graph Connectivity (Adjiashvili, Hommelsheim and
M\"uhlenthaler, "Flexible Graph Connectivity", Math. Program. pp. 1-33 (2021),
and IPCO 2020: pp. 13-26).
Let , and be integers. In an instance of the
-Flexible Graph Connectivity problem, denoted -FGC, we have an
undirected connected graph , a partition of into a set of safe
edges and a set of unsafe edges , and nonnegative costs on
the edges. A subset of edges is feasible for the -FGC
problem if for any subset of unsafe edges with , the subgraph
is -edge connected. The algorithmic goal is to find a
feasible solution that minimizes . We present a
simple -approximation algorithm for the -FGC problem via a reduction
to the minimum-cost rooted -arborescence problem. This improves on the
-approximation algorithm of Adjiashvili et al. Our -approximation
algorithm for the -FGC problem extends to a -approximation
algorithm for the -FGC problem. We present a -approximation algorithm
for the -FGC problem, and an -approximation algorithm for
the -FGC problem. Finally, we improve on the result of Adjiashvili et
al. for the unweighted -FGC problem by presenting a
-approximation algorithm.
The -FGC problem is related to the well-known Capacitated
-Connected Subgraph problem (denoted Cap-k-ECSS) that arises in the area of
Capacitated Network Design. We give a -approximation
algorithm for the Cap-k-ECSS problem, where denotes the maximum
capacity of an edge.Comment: 23 pages, 1 figure, preliminary version in the Proceedings of the
41st IARCS Annual Conference on Foundations of Software Technology and
Theoretical Computer Science (FSTTCS 2021), December 15-17, (LIPIcs, Volume
213, Article No. 9, pp. 9:1-9:14), see
https://doi.org/10.4230/LIPIcs.FSTTCS.2021.9. Related manuscript:
arXiv:2102.0330
Parameterized Approximation Schemes for Steiner Trees with Small Number of Steiner Vertices
We study the Steiner Tree problem, in which a set of terminal vertices needs
to be connected in the cheapest possible way in an edge-weighted graph. This
problem has been extensively studied from the viewpoint of approximation and
also parametrization. In particular, on one hand Steiner Tree is known to be
APX-hard, and W[2]-hard on the other, if parameterized by the number of
non-terminals (Steiner vertices) in the optimum solution. In contrast to this
we give an efficient parameterized approximation scheme (EPAS), which
circumvents both hardness results. Moreover, our methods imply the existence of
a polynomial size approximate kernelization scheme (PSAKS) for the considered
parameter.
We further study the parameterized approximability of other variants of
Steiner Tree, such as Directed Steiner Tree and Steiner Forest. For neither of
these an EPAS is likely to exist for the studied parameter: for Steiner Forest
an easy observation shows that the problem is APX-hard, even if the input graph
contains no Steiner vertices. For Directed Steiner Tree we prove that
approximating within any function of the studied parameter is W[1]-hard.
Nevertheless, we show that an EPAS exists for Unweighted Directed Steiner Tree,
but a PSAKS does not. We also prove that there is an EPAS and a PSAKS for
Steiner Forest if in addition to the number of Steiner vertices, the number of
connected components of an optimal solution is considered to be a parameter.Comment: 23 pages, 6 figures An extended abstract appeared in proceedings of
STACS 201
A Study of Arc Strong Connectivity of Digraphs
My dissertation research was motivated by Matula and his study of a quantity he called the strength of a graph G, kappa\u27( G) = max{lcub}kappa\u27(H) : H G{rcub}. (Abstract shortened by ProQuest.)
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