Çakr, H.
Using Graph Neural Networks to Solve Scheduling Problems
IDP-Arbeit
2024

Doerr, J; Pahr, A.; Grunow, M.
Exploring the Benefits of Dynamic Scheduling in Complex Manufacturing Settings
GPOM Summer 2024
2024

Kolter, Maximilian;Grunow, Martin;Kolisch, Rainer;Stäblein, Thomas
Strategic workforce and project planning for engineering automotive production systems: tackling the transition to electric vehicles
International Journal of Production Research
2024
1-21

Doerr, J; Pahr, A.; Grunow, M.
Exploring the Benefits of Dynamic Scheduling in Complex Manufacturing Settings
8th Stochastic Modelling Meeting (Milano)
EURO
2024

Becker, P.; Bottenbruch, N.
Introducing a Lead Time in Online Production Scheduling: Exploiting Correlated Uncertainties in Biomanufacturing
IDP-Arbeit
2024

Sanwald, T.
Strategic capacity planning in the biopharmaceutical industry under demand and yield uncertainty: A multi-stage stochastic programming approach
Bachelorarbeit
2023

Lakhani, J.
Strategic capacity planning in the biopharmaceutical industry under demand and yield uncertainty
2024

Schömig, M.; Grunow, M.
Increasing the Productivity of a Multi-Stage Biomanufacturing Process Using MDP Modelling
INFORMS Annual Meeting 2023 (Phoenix, USA)
2023

Zhou, L.
Building a remote server infrastructure to conduct scientific computing in operations research
IDP-Arbeit
2024

Kolter, Maximilan; Grunow, Martin; Kolisch, Rainer; Stäblein, Thomas
Strategic Workforce and Project Planning for Engineering Automotive Production Systems: Tackling the Transition to Electric Vehicles
06.06.2024