Jens Schlöter

Jens Schlöter

Universität Bremen
FB3: Mathematik/Informatik
Bibliothekstr. 5
28359 Bremen
Germany
Office: MZH 3320
Phone: +49 (421) 218-63588
Email
Office hours: by appointment

About me

I am a PhD student at the University of Bremen in Germany in the group of Prof. Dr. Nicole Megow. I am interested in scheduling problems, approximation algorithms, and combinatorial optimization in general, especially under uncertainty.

Publications

Learning-Augmented Query Policies for Minimum Spanning Tree with Uncertainty arxiv.org
Thomas Erlebach, Murilo Santos de Lima, Nicole Megow, Jens Schlöter
ESA 2022

Throughput Scheduling with Equal Additive Laxity sciencedirect.com
Martin Böhm, Nicole Megow, Jens Schlöter
Operations Research Letters 

Explorable Uncertainty Meets Decision-Making in Logistics springer.com 
Nicole Megow and Jens Schlöter
Dynamics in Logistics: 35-56, 2021  springer.com 

Robustification of Online Graph Exploration Methods  arxiv.org
Franziska Eberle, Alexander Lindermayr, Nicole Megow, Lukas Nölke, Jens Schlöter
AAAI 2022

Orienting (Hyper)graphs Under Explorable Stochastic Uncertainty  pdf
Bampis E., Dürr C., Erlebach T., de Lima M.S., Megow N., Schlöter J.
ESA 2021

Throughput Scheduling with Equal Additive Laxity springer.com
Böhm M., Megow N., Schlöter J.
CIAC 2021

On the Complexity of Conditional DAG Scheduling in Multiprocessor Systems  PDF  ieeexplore.ieee.org
Marchetti-Spaccamela A., Megow N., Schlöter J., Skutella M., Stougie L.
2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS).

Improving SAT Solving Using Monte Carlo Tree Search-based Clause Learning  springer.com
Keszöcze O., Schmitz K., Schlöter J., Drechsler R.
In: Rolf Drechsler, Mathias Soeken (Hrsg.): Advanced Boolean Techniques - Selected Papers from the 13th International Workshop on Boolean Problems, Springer International Publishing, 2019.

Preprints

Set Selection under Explorable Stochastic Uncertainty via Covering Techniques  arxiv.org
Nicole Megow and Jens Schlöter
arXiv:2211.01097, 2022.

Learning-Augmented Query Policies  arxiv.org
Erlebach T., de Lima M.S., Megow N., Schlöter J.
arXiv:2011.07385, 2020.

Theses

Schlöter, J.: Conditional Directed Acyclic Graphs: On the Complexity of Computing the Worst-Case Execution Time  PDF
Advisor: Prof. Dr. Nicole Megow, Master thesis, University of Bremen, 2019.

Schlöter, J.: Modellierung von Scheduling-Problemen mit zeitbehafteten Petri-Netzen  PDF
Advisor: Dr. Sabine Kuske, Bachelor thesis, University of Bremen, 2016.