The students understand the abstraction of networks to an attributed node-link model and are able to realize such abstractions on numerical platforms. They know the most common algorithms for solving selected problems coming from fixed- and mobile network design on this abstraction and they are able to realize these algorithms for provided data instances. Moreover, they know the most common complexity measures for such problems and are able to distinguish between easy problems, which can be solved with polynomial effort, and hard problems which have to be approximated by quality proven heuristics.

discrete mathematics, matrix calculus, combinatorics, discrete optimization theory, programming skills (MATLAB, C# or C++)

Network graphs
• Searching, sorting and connectivity in networks
• Optimal paths in networks
• Optimal spanning trees in networks
• Optimal flows in networks
• MILP modelling in networks (facility location for mobile networks, NGA fixed network design)

Lecture script as provided in the course (required); additionally, for further interested students:
D. Jungnickel: Graphs, Networks and Algorithms, Springer, 2013
H. Hamacher, K. Klamroth: Linear Network optimization, Springer, 2006
R. Ahuja, et. al.: Network flows: Theory, Algorithms and Applications, Pearson New International, 2013
M. Grötschel, et.al.: Towards optimizing the deployment of optical access

Integrated course - teaching & discussion, demonstration, exercises and practical examples in programming labs, homework

Reports on practical exercises, written/oral exam