Funded Masters thesis opportunity in collaboration with Regionales Rechenzentrum Erlangen (RRZE)

The chair of EDOM offers a

Funded Masters thesis opportunity in collaboration with Regionales Rechenzentrum Erlangen (RRZE)

Das Aufgabengebiet umfasst u. a.

We advertise a Masters thesis that is funded. No funding is available without writing a thesis!


In a recent Masters thesis, we studied the optimization problem of allocating resources from facilities to users in a fair manner. The motivation of the problem is the positioning of recycling centers (or, “Wertstoffhöfe”) in a manner that places fair loads on the facilities, yet is accessible to the public. Details are available here:

http://www.optimization-online.org/DB_HTML/2021/1/8669.html.


This proposed thesis builds on one component of the previous work. In the previous work, we designed a greedy algorithm that achieves solutions to this problem quickly. Greedy algorithms are a class of algorithms that provide the maximum
bang-for-buck benefit, that only look ahead for an immediate maximum gain, and are often suboptimal. The specific task of this Masters thesis is to improve this algorithm. Other additions are encouraged as well.


The computational aspects of the thesis would be fostered with a close collaboration with scientists and programmers from the Regional Computer Center Erlangen (RRZE); i.e., the student has a unique opportunity to spend time at RRZE
as well. Part of the thesis is funded and the student would be financially supported as a HiWi with a grant by the mentor from the Bavarian Ministry of Science and Arts.


Some existing code is available in Python and Pyomo; however the student is free to rewrite this code in any language
of his/her choice. Knowledge of a modeling language such as GAMS or Pyomo is essential. The thesis also requires a good
understanding of optimization models, and a background in discrete optimization and/or algorithms is helpful.


Professional group: (For example Student Assistant)
Masters students in Mathematics, Computer Science and/or closely related areas seeking to write their thesis can be funded as a Student Assistant


The field of activity includes:

1. read and understand existing work plus existing code with assistance of the mentor;

2. develop codes in any programming language (preferably Pyomo or GAMS) of the student’s choice;

3. scale existing model from the state of Bavaria to the entire Germany;

4. implement the code on High Performance Computing (HPC) clusters at RRZE with assistance of RRZE’s scientists;

5. write a report summarizing the results.

Notwendige Qualifikation

Excellent knowledge of a programming language (such as Python, R, C++, etc.) and a working knowledge of a modeling language (such as GAMS or Pyomo).

Excellent grades.

Wünschenswerte Qualifikation

A lecture on Discrete Mathematics or Discrete Optimization

Bemerkungen

The student would be actively assisted by the mentor and researchers at RRZE. A high quality thesis can also be developed into a research article with the student as a leading author. Writing a funded masters thesis for this subject, assisted by a group of actively involved researchers, offers the student a unique opportunity for his/her professional career.

Bewerbungsschluss
01.10.2022

Detailinformationen

Stellenbezeichnung
Funded Masters thesis opportunity in collaboration with Regionales Rechenzentrum Erlangen (RRZE)
Besetzung zum
immediate

Teilzeit / Vollzeit
Teilzeit
Wochenarbeitszeit
up to 19h/week
Reason for limitation
befristetes Forschungsvorhaben

Kontaktperson für weitere Informationen
Dr. Bismark Singh
Telefon: 09131 85-67186
E-Mail: bismark.singh@fau.de
Link: https://www.datascience.nat.fau.eu/research/groups/amio/members/bismark-singh/
Lehrstuhl für Analytics & Mixed-Integer Optimization
Cauerstraße 11
91058 Erlangen Bayern
Übersicht

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