Kreuzungen in Cluster-Level-Graphen

Clustered graphs are an enhanced graph model with a recursive clustering of the vertices according to a given nesting relation. This prime technique for expressing coherence of certain parts of the graph is used in many applications, such as biochemical pathways and UML class diagrams. For directed clustered graphs usually level drawings are used, leading to clustered level graphs. In this thesis we analyze the interrelation of clusters and levels and their influence on edge crossings and cluster/edge crossings.Cluster-Graphen sind ein erweitertes Graph-Modell mit einem rekursiven Clustering der Knoten entsprechend einer gegebenen Inklusionsrelation. Diese bedeutende Technik um Zusammengehörigkeit bestimmter Teile des Graphen auszudrücken wird in vielen Anwendungen benutzt, etwa biochemischen Reaktionsnetzen oder UML Klassendiagrammen. Für gerichtete Cluster-Graphen werden üblicherweise Level-Zeichnungen verwendet, was zu Cluster-Level-Graphen führt. Diese Arbeit analysiert den Zusammenhang zwischen Clustern und Level und deren Auswirkungen auf Kantenkreuzungen und Cluster/Kanten-Kreuzungen

Logic learning and optimized drawing: two hard combinatorial problems

Nowadays, information extraction from large datasets is a recurring operation in countless fields of applications. The purpose leading this thesis is to ideally follow the data flow along its journey, describing some hard combinatorial problems that arise from two key processes, one consecutive to the other: information extraction and representation. The approaches here considered will focus mainly on metaheuristic algorithms, to address the need for fast and effective optimization methods. The problems studied include data extraction instances, as Supervised Learning in Logic Domains and the Max Cut-Clique Problem, as well as two different Graph Drawing Problems. Moreover, stemming from these main topics, other additional themes will be discussed, namely two different approaches to handle Information Variability in Combinatorial Optimization Problems (COPs), and Topology Optimization of lightweight concrete structures

k-Layer Straightline Crossing Minimization by Speeding Up Sifting

Recently, a technique called sifting has been proposed for k-layer straightline crossing minimization. This approach outperforms the traditional layer by layer sweep based heuristics by far when applied to k-layered graphs with $k\geq 3$. In this paper, we present two methods to speed up sifting. First, it is shown how the crossing matrix can be computed and updated efficiently. Then, we study lower bounds which can be incorporated in the sifting algorithm, allowing to prune large parts of the search space. Experimental results show that it is possible to speed up sifting by more than a factor of 20 using the new methods

Visualisierung biochemischer Reaktionsnetze

In dieser Arbeit werden Anforderungen an die Darstellung biochemischer Reaktionsnetze untersucht und die Netze unter dem Gesichtspunkt der Visualisierung modelliert. Anschliessend wird ein Algorithmus zum Zeichnen biochemischer Reaktionsnetze entwickelt und analysiert.In this dissertation we investigate the requirements for the visualisation of biochemical reaction networks. We compose a model for these networks that lends itself to visualisation and develop and analyse an algorithm to create drawings of the networks