Sven Jäger

I am a postdoctoral researcher in combinatorial optimization at the Optimization Research Group of the RPTU in Kaiserslautern. My research is mainly concerned with machine scheduling and, more recently, optimization in public transport.

Between 2016 and 2021, I did my PhD in the COGA Group at TU Berlin under the supervision of Martin Skutella. Afterwards, I worked for one year in the Optimization Division of the Fraunhofer Institute for Industrial Mathematics.


Journal Articles

Conference Proceedings

PhD Thesis



Competitive Kill-and-Restart and Preemptive Strategies for Non-clairvoyant Scheduling

Research Seminar, Optimization Group, TU Kaiserslautern

No slides available
Scheduling Unrelated Parallel Machines with Attribute-Dependent Setup Times: a Case Study

Operations Resarch 2022


In the summer semester 2023 I will supervise two groups during their Fachpraktikum.

In the past I was involved in the following courses.

Computerorientierte Mathematik I

First course on algorithms and programming for math bachelor students.

Topics: running time, number representations, binary search, graphs, sorting, Gaussian elimination, spanning trees, matroids, dynamic programming, introduction to programming

Computerorientierte Mathematik II

Second course on algorithms and programming for math bachelor students.

Topics: data structures, Huffman codes, shortest paths, Turing machines, computability, complexity, object orientation

Introduction to Linear and Combinatorial Optimization (ADM I)

Introductory course for math bachelor and master students.

Topics: Simplex algorithm, LP duality, paths and trees, maximum flows, min-cost flows, maximum bipartite matchings, stable matchings, ellipsoid method, large-scale linear programming, sensitivity analysis

Discrete Optimization (ADM II)

Advanced course for math bachelor and master students.

Topics: Branchings and arborescences, maximum matchings, minimum-cost perfect matchings, T-joins, matroids, total unimodularity, total dual integrality, Gomory-Chvátal cutting planes, branch-and-bound algorithm, Lagrangian dual, subgradient method

Plain Academic