Topics for Bachelor Theses

We have numerous topics available that are suitable for doing a Bachelor Thesis. Some example topics are provided on this page, but interested students are encouraged to directly contact a potential supervisor by email regarding the choice of a suitable topic. This email should also include a recent list of your grades (Sammelzeugnis).

Cooperative Optimization Approaches for Distributing Service Points

Contact: Thomas Jatschka or Günther Raidl

For many business models an optimal distribution of service points in a customer community is needed. Examples are charging/battery swapping stations of electric vehicles, bicycle/car sharing stations, and repair stations. When planning such systems, estimating under which conditions which customer demand can be fulfilled is fundamental in order to design and evaluate possible solutions. Such customer demands are usually acquired upfront e.g. using data on public transport, the street network, or surveys of potential customers. However, customer demand information determined in such ways typically is vague, and not uncommonly a system built on such assumptions is not as effective as originally hoped for due to major deviations in reality.

Alternative to acquiring demands upfront, cooperative optimization approaches incorporate potential users directly into the data acquisition as well as the optimization process. Expected benefits are a faster and cheaper data acquisition, the direct integration of users into the whole planning process, and ultimately better and more accepted optimization results. However, integrating users into the optimization progress also comes with some disadvantages. User interactions are not only considered time consuming but should also be treated as a scarce resource as a user is only willing to have a limited number of interactions with the program. A possible way to overcome these limitations is to use surrogate functions/machine learning techniques for simulating the interaction with a user.

 

Solving Hard Combinatorial Problems with SAT and QBF Solvers

Contact: Stefan Szeider

Over the last two decades, SAT-solvers (which are programs that solve the Boolean satisfiability problem) have become surprisingly powerful and can check the satisfiability of instances with hundreds of thousands of variables in a few minutes. Among the most powerful SAT-solvers are Glucose and Lingeling.The subject for a Bachelor or Masters thesis would be to translate a hard combinatorial problem into SAT and solve it with a SAT-solver. For such a translation (often called encoding) there are usually many different approaches, and part of the thesis would be to compare different approaches experimentally on a set of problem instances.

The considered combinatorial problem can be chosen from a large pool of problems, including graph, clustering and optimization problems. Some recent research in this direction can be found here and here.

For even harder problems, like finding a winning strategy for a board game, one needs to go beyond SAT and use a QBF solver (Qute is such a solver we developed in our group).

 

Graph Drawing

Contact: Martin Nöllenburg

Graph Drawing is concerned with algorithms to compute geometric representations of graphs and networks. Applications of graph drawing range from graph visualizations for human users to hardware layouts and wireless routing. Scientifically, the area offers a wide spectrum of topics for student theses, from theoretical questions (e.g., existence of certain layouts or algorithms with certain properties) to practical questions of modeling the actual requirements of a particular application and designing, implementing, and evaluating algorithms for solving it.

Requirements:

• Proficiency in (graph) algorithmics
• Interest in geometry and visualization
• Practical topics: good programming skills

Algorithmic Cartography and Geometry

Contact: Martin Nöllenburg

Digital cartography offers a wide spectrum of visualization problems that can be solved by geometric algorithms. The types of maps range from dynamic and interactive maps, e.g., on smart phones and mobile devices, to unconventional diagrammatic or schematic maps. Examples of algorithmic problems comprise label placement for map features, algorithms for constructing cartograms, or schematic destination maps. The area contains both topics with a stronger practical focus (including evaluation) or with a more theoretical focus. Thesis topics in computational geometry without direct links to cartography are also possible.

Requirements:

• Proficiency in algorithmics and geometric algorithms
• Interest in maps and interdisciplinary work
• Practical topics: good programming skills

Analysis of Structural Properties

Contact: Robert Ganian

Many instances of NP-hard problems that need to be solved in real-world settings implicitly contain structural properties which can be exploited to obtain efficient and exact solutions. However, it is often difficult to identify precisely what sort of structure the instances of interest possess. To help in this endeavour, it is highly desirable to perform an algorithmic analysis of studied instances of various prominent problems (for instance available in the form of benchmark sets) in order to determine their structural properties.

Requirements:

• Proficiency in English
• Good programming skills
• Interest in (graph) algorithms