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Master Thesis (f/m/x) - Multi-Criteria selection of configurations in Trade-off Analysis
Job Description
Req ID:  6111
Place of work:  Braunschweig
Starting date:  At the earliest opportunity
Career level:  Student research project and final thesis
Type of employment:  Part time, Full-time
Duration of contract:  3-6 months

Remuneration: Remuneration is in accordance with the Collective Agreement for the Public Sector - Federal Government (TVöD-Bund)

Enter the fascinating world of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e. V.; DLR) and help shape the future through research and innovation! We offer an exciting and inspiring working environment driven by the expertise and curiosity of our 12,000 employees from 100 nations and our unique infrastructure. Together, we develop sustainable technologies and thus contribute to finding solutions to global challenges. Would you like to join us in addressing this major future challenge? Then this is your place!

The DLR Institute of Software Technology sees software as a catalyst for research and innovation. The institute's staff, currently numbering around 200, make a significant contribution to advancements in the fields of aviation, space, energy, transportation, and security through the development of state-of-the-art software solutions and innovative research.

Our areas of competence include reliable and safety-critical software systems, artificial intelligence, high-performance computing and quantum computing, human-system interaction and visualisation, software and systems engineering as well as digital platforms and digital twins.

 

What to expect

During the design of space systems, trade-off analysis is carried out to evaluate conflicting objectives and identify optimal configurations. After configurations are identified, it is still important to understand how and why a configuration should be selected. Multi-Criteria Decision-Making (MCDM) provide methods such as weighted-sum, epsilon constraints, and TOPSIS, to rank and select configurations. This thesis investigates existing MCDM techniques and applies them to configurations derived from an inhouse digital twin tool designed for identifying and analyzing configurations. A prototype will be implemented to evaluate the selected method and recommendatations should be provided.

 

Your tasks

  • Literature review on existing MCDM methods for ranking and selecting Pareto-optimal configurations
  • Identify common challenges and limitations of these methods when applied to conflicting objectives 
  • Select and implement two to three representative MCDM methods (e.g weighted-sum, epsilon-constraint, TOPSIS)
  • Apply the selected methods to sets of Pareto-optimal configurations from case studies and evaluate the methods in terms of its ability to effectively compare configurations

 

Your profile

  • You are studying in Computer Science, Systems Engineering, or similar courses. 
  • You own good knowledge in programming languages, preferably in Python. 
  • You have interest in decision theory, multi-objective optimization, or trade-off analysis. 
  • And you are a team player with creativity, independence and personal responsibility.

We offer

DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.

 

We look forward to getting to know you!

 

If you have any questions about this position (Vacancy-ID 6111) please contact:

 

Frank Eric Mbouga 
Apply now