22 citations · 25 across the 4 of their papers we have counts for
5 papers
APEX: An Extensible Model for Agent-Assisted Production Scheduling
Felix J. Grumbach, Stefan Görlitz
Production scheduling requires realistic models that reflect operational constraints and efficient methods that balance competing goals. Putting these methods into use also require…
Demystifying Reinforcement Learning in Production Scheduling via Explainable AI
Daniel Fischer, Hannah M. Hüsener, Felix Grumbach +3
Deep Reinforcement Learning (DRL) is a frequently employed technique to solve scheduling problems. Although DRL agents ace at delivering viable results in short computing times, th…
Smaller Batches, Bigger Gains? Investigating the Impact of Batch Sizes on Reinforcement Learning Based Real-World Production Scheduling
Arthur Müller, Felix Grumbach, Matthia Sabatelli
Production scheduling is an essential task in manufacturing, with Reinforcement Learning (RL) emerging as a key solution. In a previous work, RL was utilized to solve an extended p…
Optimizing Sales Forecasts through Automated Integration of Market Indicators
Lina Döring, Felix Grumbach, Pascal Reusch
Recognizing that traditional forecasting models often rely solely on historical demand, this work investigates the potential of data-driven techniques to automatically select and i…
A Memetic Algorithm with Reinforcement Learning for Sociotechnical Production Scheduling
Felix Grumbach, Nour Eldin Alaa Badr, Pascal Reusch +1
The following interdisciplinary article presents a memetic algorithm with applying deep reinforcement learning (DRL) for solving practically oriented dual resource constrained flex…