Master Thesis (f/m/x) - Multi-Criteria selection of configurations in Trade-off Analysis
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Deine Aufgaben
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.
- 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
Dein Profil
- 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.
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.
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