
Feedback Edge Sets in Temporal Graphs
The classical, lineartime solvable Feedback Edge Set problem is concern...
read it

The Complexity of Finding Temporal Separators under Waiting Time Constraints
In this work, we investigate the computational complexity of Restless Te...
read it

Multistage Vertex Cover
Covering all edges of a graph by a minimum number of vertices, this is t...
read it

Comparing Temporal Graphs Using Dynamic Time Warping
The connections within many realworld networks change over time. Thus, ...
read it

Temporal Graph Classes: A View Through Temporal Separators
We investigate the computational complexity of separating two distinct v...
read it

Multistage Problems on a Global Budget
Timeevolving or temporal graphs gain more and more popularity when stud...
read it

Multistage Graph Problems on a Global Budget
Timeevolving or temporal graphs gain more and more popularity when stud...
read it
On Finding Separators in Temporal Split and Permutation Graphs
Removing all connections between two vertices s and z in a graph by removing a minimum number of vertices is a fundamental problem in algorithmic graph theory. This (s,z)separation problem is wellknown to be polynomial solvable and serves as an important primitive in many applications related to network connectivity. We study the NPhard temporal (s,z)separation problem on temporal graphs, which are graphs with fixed vertex sets but edge sets that change over discrete time steps. We tackle this problem by restricting the layers (i.e., graphs characterized by edges that are present at a certain point in time) to specific graph classes. We restrict the layers of the temporal graphs to be either all split graphs or all permutation graphs (both being perfect graph classes) and provide both intractability and tractability results. In particular, we show that in general the problem remains NPhard both on temporal split and temporal permutation graphs, but we also spot promising islands of fixedparameter tractability particularly based on parameterizations that measure the amount of "change over time".
READ FULL TEXT
Comments
There are no comments yet.