121 research outputs found
Computational Complexity of Synchronization under Regular Commutative Constraints
Here we study the computational complexity of the constrained synchronization
problem for the class of regular commutative constraint languages. Utilizing a
vector representation of regular commutative constraint languages, we give a
full classification of the computational complexity of the constraint
synchronization problem. Depending on the constraint language, our problem
becomes PSPACE-complete, NP-complete or polynomial time solvable. In addition,
we derive a polynomial time decision procedure for the complexity of the
constraint synchronization problem, given some constraint automaton accepting a
commutative language as input.Comment: Published in COCOON 2020 (The 26th International Computing and
Combinatorics Conference); 2nd version is update of the published version and
1st version; both contain a minor error, the assumption of maximality in the
NP-c and PSPACE-c results (propositions 5 & 6) is missing, and of
incomparability of the vectors in main theorem; fixed in this version. See
(new) discussion after main theore
On the complement graph and defensive k-alliances
AbstractIn this paper, we obtain several tight bounds of the defensive k-alliance number in the complement graph from other parameters of the graph. In particular, we investigate the relationship between the alliance numbers of the complement graph and the minimum and maximum degree, the domination number and the isoperimetric number of the graph. Moreover, we prove the NP-completeness of the decision problem underlying the defensive k-alliance number
Fast branching algorithm for Cluster Vertex Deletion
In the family of clustering problems, we are given a set of objects (vertices
of the graph), together with some observed pairwise similarities (edges). The
goal is to identify clusters of similar objects by slightly modifying the graph
to obtain a cluster graph (disjoint union of cliques). Hueffner et al. [Theory
Comput. Syst. 2010] initiated the parameterized study of Cluster Vertex
Deletion, where the allowed modification is vertex deletion, and presented an
elegant O(2^k * k^9 + n * m)-time fixed-parameter algorithm, parameterized by
the solution size. In our work, we pick up this line of research and present an
O(1.9102^k * (n + m))-time branching algorithm
Ordering a sparse graph to minimize the sum of right ends of edges
Motivated by a warehouse logistics problem we study mappings of the vertices of a graph onto prescribed points on the real line that minimize the sum (or equivalently, the average) of the coordinates of the right ends of all edges. We focus on graphs whose edge numbers do not exceed the vertex numbers too much, that is, graphs with few cycles. Intuitively, dense subgraphs should be placed early in the ordering, in order to finish many edges soon. However, our main “calculation trick” is to compare the objective function with the case when (almost) every vertex is the right end of exactly one edge. The deviations from this case are described by “charges” that can form “dipoles”. This reformulation enables us to derive polynomial algorithms and NP-completeness results for relevant special cases, and FPT results
Alliance free and alliance cover sets
A \emph{defensive} (\emph{offensive}) -\emph{alliance} in
is a set such that every in (in the boundary of ) has
at least more neighbors in than it has in . A set
is \emph{defensive} (\emph{offensive}) -\emph{alliance free,}
if for all defensive (offensive) -alliance , ,
i.e., does not contain any defensive (offensive) -alliance as a subset.
A set is a \emph{defensive} (\emph{offensive})
-\emph{alliance cover}, if for all defensive (offensive) -alliance ,
, i.e., contains at least one vertex from each
defensive (offensive) -alliance of . In this paper we show several
mathematical properties of defensive (offensive) -alliance free sets and
defensive (offensive) -alliance cover sets, including tight bounds on the
cardinality of defensive (offensive) -alliance free (cover) sets
Nova Geminorum 1912 and the Origin of the Idea of Gravitational Lensing
Einstein's early calculations of gravitational lensing, contained in a
scratch notebook and dated to the spring of 1912, are reexamined. A hitherto
unknown letter by Einstein suggests that he entertained the idea of explaining
the phenomenon of new stars by gravitational lensing in the fall of 1915 much
more seriously than was previously assumed. A reexamination of the relevant
calculations by Einstein shows that, indeed, at least some of them most likely
date from early October 1915. But in support of earlier historical
interpretation of Einstein's notes, it is argued that the appearance of Nova
Geminorum 1912 (DN Gem) in March 1912 may, in fact, provide a relevant context
and motivation for Einstein's lensing calculations on the occasion of his first
meeting with Erwin Freundlich during a visit in Berlin in April 1912. We also
comment on the significance of Einstein's consideration of gravitational
lensing in the fall of 1915 for the reconstruction of Einstein's final steps in
his path towards general relativity.Comment: 31 p
Towards Optimal and Expressive Kernelization for d-Hitting Set
d-Hitting Set is the NP-hard problem of selecting at most k vertices of a
hypergraph so that each hyperedge, all of which have cardinality at most d,
contains at least one selected vertex. The applications of d-Hitting Set are,
for example, fault diagnosis, automatic program verification, and the
noise-minimizing assignment of frequencies to radio transmitters.
We show a linear-time algorithm that transforms an instance of d-Hitting Set
into an equivalent instance comprising at most O(k^d) hyperedges and vertices.
In terms of parameterized complexity, this is a problem kernel. Our
kernelization algorithm is based on speeding up the well-known approach of
finding and shrinking sunflowers in hypergraphs, which yields problem kernels
with structural properties that we condense into the concept of expressive
kernelization.
We conduct experiments to show that our kernelization algorithm can kernelize
instances with more than 10^7 hyperedges in less than five minutes.
Finally, we show that the number of vertices in the problem kernel can be
further reduced to O(k^{d-1}) with additional O(k^{1.5 d}) processing time by
nontrivially combining the sunflower technique with d-Hitting Set problem
kernels due to Abu-Khzam and Moser.Comment: This version gives corrected experimental results, adds additional
figures, and more formally defines "expressive kernelization
A Satisfiability-based Approach for Embedding Generalized Tanglegrams on Level Graphs
A tanglegram is a pair of trees on the same set of leaves with matching leaves in the two trees joined by an edge. Tanglegrams are widely used in computational biology to compare evolutionary histories of species. In this paper we present a formulation of two related combinatorial embedding problems concerning tanglegrams in terms of CNF-formulas. The first problem is known as planar embedding and the second as crossing minimization problem. We show that our satisfiability formulation of these problems can handle a much more general case with more than two, not necessarily binary or complete, trees defined on arbitrary sets of leaves and allowed to vary their layouts
Linear-time Algorithms for Eliminating Claws in Graphs
Since many NP-complete graph problems have been shown polynomial-time
solvable when restricted to claw-free graphs, we study the problem of
determining the distance of a given graph to a claw-free graph, considering
vertex elimination as measure. CLAW-FREE VERTEX DELETION (CFVD) consists of
determining the minimum number of vertices to be removed from a graph such that
the resulting graph is claw-free. Although CFVD is NP-complete in general and
recognizing claw-free graphs is still a challenge, where the current best
algorithm for a graph has the same running time of the best algorithm for
matrix multiplication, we present linear-time algorithms for CFVD on weighted
block graphs and weighted graphs with bounded treewidth. Furthermore, we show
that this problem can be solved in linear time by a simpler algorithm on
forests, and we determine the exact values for full -ary trees. On the other
hand, we show that CLAW-FREE VERTEX DELETION is NP-complete even when the input
graph is a split graph. We also show that the problem is hard to approximate
within any constant factor better than , assuming the Unique Games
Conjecture.Comment: 20 page
On cycle transversals and their connected variants in the absence of a small linear forest.
A graph is H-free if it contains no induced subgraph isomorphic to H. We prove new complexity results for the two classical cycle transversal problems Feedback Vertex Set and Odd Cycle Transversal by showing that they can be solved in polynomial time for (sP1+P3) -free graphs for every integer s≥1 . We show the same result for the variants Connected Feedback Vertex Set and Connected Odd Cycle Transversal. For the latter two problems we also prove that they are polynomial-time solvable for cographs; this was known already for Feedback Vertex Set and Odd Cycle Transversal
- …