One of the core tasks of engineering is optimising technical processes. Virtually all engineering optimisation tasks involve considering competing objectives. In multi-objective optimisation (MOO), these competing objectives are explicitly considered rather than being combined into a single objective function, as is usually the case. The outcome of MOO is a set of Pareto-optimal solutions, which are defined as solutions where no objective can be improved without deteriorating at least one other objective. In process design, only these solutions are of interest, and engineers can choose the one best suited to the task at hand. This opens up new possibilities for process design.

The present project is carried out in the research training group MIMO, which is funded by the Deutsche Forschungsgemeinschaft (DFG). In this group, mathematicians and engineers work closely together (see math.rptu.de/en/rtg-2982). In the project, we will develop methods for applying MOO to process engineering tasks. In MOO problems from engineering that we have previously studied, we consistently found unusual, unexpected topologies of the Pareto set. We will further explore these intriguing findings and develop ways to actively use them in MOO. A second line of exploration relates to dimensionless numbers, such as the well-known Reynolds number. Preliminary work has shown us that combining MOO and dimensionless numbers offers novel opportunities for MOO in engineering.

We welcome applications from candidates from engineering, physics and mathematics. The unique environment of MIMO ensures excellent on-the-job training.

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