Learning Reduced Order Dynamics via Geometric Representations
Imran Nasim, Melanie Weber
SCML 2024
We built and deployed a decision-support system for scheduling paper manufacturing and distribution, an extremely complex task with multiple stages of production and strong interaction between stages. In contrast to earlier approaches, our system considers multiple scheduling objectives and multiple stages of production and distribution simultaneously using multiple evaluation criteria. Our system functions as an intelligent assistant to the schedulers and generates multiple good scheduling alternatives using a portfolio of algorithms and direct human-expert input. The successful deployment of our system at several paper mills in North America has resulted in significant savings, greater customer satisfaction, and improved business processes.
Imran Nasim, Melanie Weber
SCML 2024
U. Wieser, U. Kunze, et al.
Physica E: Low-Dimensional Systems and Nanostructures
Frank Stem
C R C Critical Reviews in Solid State Sciences
J.K. Gimzewski, T.A. Jung, et al.
Surface Science