Master Thesis (f/m/x) - Multi-Criteria selection of configurations in Trade-off Analysis

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 look forward to getting to know you! If you have any questions about this position (Vacancy-ID 6111 ) please

contact:

Frank Eric Mbouga