Photo

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 one year in the Optimization Division of the Fraunhofer Institute for Industrial Mathematics.

This winter semester I give a lecture on Algorithmic Game Theory. More information is provided on the OpenOlat course page. The password is the RPTU math standard password.

Publications

Journal Articles

Conference Proceedings

PhD Thesis

Unpublished

Sven Jäger

My coauthors

Talks

Slides
Delay Management on a Path

Operations Research (OR) 2023, 

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

Highlights of Algorithms (HALG) 2023, 

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Modelling multi-modal transport planning

Hot Topic workshop “Integrated Planning in Public Transport”, 

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

Operations Resarch (OR) 2022, 

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Approximation in Deterministic and Stochastic Machine Scheduling

PhD Defense, 

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Scheduling Stochastic Jobs with Release Dates on a Single Machine

Dagstuhl Seminar 20081 Scheduling, 

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On orthogonal symmetric chain decompositions

European Conference on Combinatorics, Graph Theory and Applications (EUROCOMB) 2019, 

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Generalizing the Kawaguchi-Kyan Bound to Stochastic Parallel Machine Scheduling

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Approximating Total Weighted Completion Time on Identical Parallel Machines with Precedence Constraints and Release Dates

Workshop on Models and Algorithms for Planning and Scheduling (MAPSP) 2019, 

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Gray codes and symmetric chains

45th International Colloquium on Automata, Languages, and Programming (ICALP 2018), 

Teaching

In the winter semester 2023/24 I am giving a lecture on Algorithmic Game Theory.

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