Enable autonomous, unsupervised experiments at synchrotrons/neutron instruments
Develop the embedded compute and control building blocks that allow experiments to run with minimal human intervention, including reliable real-time execution, monitoring, and safe closed-loop operation.
 

Optimize beamtime through low-latency closed-loop control
Reduce the decision-to-actuation cycle by implementing fast on-the-fly data processing and control-path integration so the experiment converges to informative settings with fewer trial measurements.
 

Implement self-adjusting experimental parameters driven by rapid data analysis
Design and deploy real-time pipelines that extract key metrics (quality indicators, uncertainty, drift/damage cues) and translate them into automatic parameter updates (scan points, exposure, attenuation, ROI/mask updates, etc.).
 

In order to implement the insights of the project to hospitals, a suitable interface for personnel planning software is necessary. Therefore the correlations between education and personnel planning are analyzed and mapped to an interdependency matrix. This also helps with identifying and avoiding potential problems and intends to simplify future research.
Additionally, a guideline for researchers and practitioners sums up the arising problems in resident planning to help them understand the complexity of planning.

A clear educational structure and reliable planning improves a hospitals reputation for attractive and efficient education and thus providing a competitive advantage in employing physicians. However, hospitals need to consider high service levels and the effective use of human resources. Paying attention to all of these aspects means in a first step to determine the optimal number of education appointments with consideration of resource and capacity limitations. Due to the planning complexity, mathematical models and methods are used to first determine the optimal number of resident jobs along with the appropriate education schedules. Therefore a mixed integer problem is formulated and solved with OR/MS algorithms, like column generation, branch, price and cut or Benders decomposition. The developed methods are tested within simulations as well as case studies at the cooperation partner.

After developing the mathematical model for resident scheduling, the problem is expanded by stochastic factors that occur in reality and affect demands and capacities. Therefore on the one hand, Markov decision processes are used and on the other hand, a two-stage stochastic programming approach, which intends to provide more ex-ante information. The formerly developed methods need to be adapted to these topics.
However, uncertainties occur not only within the strategical planning but also within the tactical planning level, where the educational schedule is transformed into a concrete working roster. In this context, certainty measurements help to avoid unfairness in terms of steady progress or number of clinic transitions.
Overall, the uncertainties regarding the number of surgeries are intended to be met by a robustness concept in order to improve planning reliability and lower the number of roster changes.

Since fairness directly affects employees’ satisfaction and thus the quality of work, different fairness concepts are defined and their influence on personnel planning is evaluated. In this context, especially the number of clinic transitions and the intended influence on the continuity of care is considered. Therefore the developed models are adapted and solved heuristically, for example with local search heuristics.