10,395 research outputs found
Parameterized Complexity of Graph Constraint Logic
Graph constraint logic is a framework introduced by Hearn and Demaine, which
provides several problems that are often a convenient starting point for
reductions. We study the parameterized complexity of Constraint Graph
Satisfiability and both bounded and unbounded versions of Nondeterministic
Constraint Logic (NCL) with respect to solution length, treewidth and maximum
degree of the underlying constraint graph as parameters. As a main result we
show that restricted NCL remains PSPACE-complete on graphs of bounded
bandwidth, strengthening Hearn and Demaine's framework. This allows us to
improve upon existing results obtained by reduction from NCL. We show that
reconfiguration versions of several classical graph problems (including
independent set, feedback vertex set and dominating set) are PSPACE-complete on
planar graphs of bounded bandwidth and that Rush Hour, generalized to boards, is PSPACE-complete even when is at most a constant
The Complexity of Change
Many combinatorial problems can be formulated as "Can I transform
configuration 1 into configuration 2, if certain transformations only are
allowed?". An example of such a question is: given two k-colourings of a graph,
can I transform the first k-colouring into the second one, by recolouring one
vertex at a time, and always maintaining a proper k-colouring? Another example
is: given two solutions of a SAT-instance, can I transform the first solution
into the second one, by changing the truth value one variable at a time, and
always maintaining a solution of the SAT-instance? Other examples can be found
in many classical puzzles, such as the 15-Puzzle and Rubik's Cube.
In this survey we shall give an overview of some older and more recent work
on this type of problem. The emphasis will be on the computational complexity
of the problems: how hard is it to decide if a certain transformation is
possible or not?Comment: 28 pages, 6 figure
Shortest Reconfiguration of Sliding Tokens on a Caterpillar
Suppose that we are given two independent sets I_b and I_r of a graph such
that |I_b|=|I_r|, and imagine that a token is placed on each vertex in |I_b|.
Then, the sliding token problem is to determine whether there exists a sequence
of independent sets which transforms I_b into I_r so that each independent set
in the sequence results from the previous one by sliding exactly one token
along an edge in the graph. The sliding token problem is one of the
reconfiguration problems that attract the attention from the viewpoint of
theoretical computer science. The reconfiguration problems tend to be
PSPACE-complete in general, and some polynomial time algorithms are shown in
restricted cases. Recently, the problems that aim at finding a shortest
reconfiguration sequence are investigated. For the 3SAT problem, a trichotomy
for the complexity of finding the shortest sequence has been shown, that is, it
is in P, NP-complete, or PSPACE-complete in certain conditions. In general,
even if it is polynomial time solvable to decide whether two instances are
reconfigured with each other, it can be NP-complete to find a shortest sequence
between them. Namely, finding a shortest sequence between two independent sets
can be more difficult than the decision problem of reconfigurability between
them. In this paper, we show that the problem for finding a shortest sequence
between two independent sets is polynomial time solvable for some graph classes
which are subclasses of the class of interval graphs. More precisely, we can
find a shortest sequence between two independent sets on a graph G in
polynomial time if either G is a proper interval graph, a trivially perfect
graph, or a caterpillar. As far as the authors know, this is the first
polynomial time algorithm for the shortest sliding token problem for a graph
class that requires detours
A Dichotomy Theorem for Circular Colouring Reconfiguration
The "reconfiguration problem" for circular colourings asks, given two
-colourings and of a graph , is it possible to transform
into by changing the colour of one vertex at a time such that every
intermediate mapping is a -colouring? We show that this problem can be
solved in polynomial time for and is PSPACE-complete for
. This generalizes a known dichotomy theorem for reconfiguring
classical graph colourings.Comment: 22 pages, 5 figure
The complexity of dominating set reconfiguration
Suppose that we are given two dominating sets and of a graph
whose cardinalities are at most a given threshold . Then, we are asked
whether there exists a sequence of dominating sets of between and
such that each dominating set in the sequence is of cardinality at most
and can be obtained from the previous one by either adding or deleting
exactly one vertex. This problem is known to be PSPACE-complete in general. In
this paper, we study the complexity of this decision problem from the viewpoint
of graph classes. We first prove that the problem remains PSPACE-complete even
for planar graphs, bounded bandwidth graphs, split graphs, and bipartite
graphs. We then give a general scheme to construct linear-time algorithms and
show that the problem can be solved in linear time for cographs, trees, and
interval graphs. Furthermore, for these tractable cases, we can obtain a
desired sequence such that the number of additions and deletions is bounded by
, where is the number of vertices in the input graph
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