Graphs are a simple mathematical model that is widely used to model real-world systems and phenomena. A graph consists of a set of objects, called vertices, and a set of edges connecting pairs of vertices. The set of vertices could be a group of people with edges representing whether two people know each other or the vertices could correspond to web pages and the edges correspond to hyperlinks between webpages.
Graphs can be distinguished between undirected and directed graphs, depending on whether the edges always go in both directions, such as in the example of people knowing each other, or can be directed only in one direction such as in the hyperlink example.
The elegance of graphs as mathematical abstraction is their simplicity, which allows to abstract from many irrelevant details of real practical problem instances.
One of the early observations in computer science was that many algorithmic problems are computationally intractable, formalised by the mathematical concept of "NP-hardness". This includes many algorithmic problems that frequently occur in practice. A particularly rich class of these problems can elegantly be formalised using the concepts of graphs.
One very successful way to overcome the computational hardness of many algorithmic problems on graphs is to study classes of graphs that have a particularly simple structure. A prominent example are planar graphs that can be drawn on a sheet of paper without edges crossing each other. It turned out that this structure can be exploited to design highly efficient algorithms for hard computational problems on input instances that are planar graphs. This has led to a very well developed theory of structural properties of graphs that can be used in the design of efficient algorithms.
However, much of this work has focussed on undirected graphs. The goal of this project is to generalise a part of this theory, known as graph minor theory and nowhere denseness, to directed graphs. In this way, the objective is to make this structural theory of graphs applicable also for algorithmic problems that are naturally modelled as directed graphs.