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cs.LG2026
Solving the Paint Shop Problem with Flexible Management of Multi-Lane Buffers Using Reinforcement Learning and Action Masking
Mirko Stappert, Bernhard Lutz, Janis Brammer +1
In the paint shop problem, an unordered incoming sequence of cars assigned to different colors has to be reshuffled with the objective of minimizing the number of color changes. To…
cs.LG2025
Discovering and Analyzing Stochastic Processes to Reduce Waste in Food Retail
Anna Kalenkova, Lu Xia, Dirk Neumann
This paper proposes a novel method for analyzing food retail processes with a focus on reducing food waste. The approach integrates object-centric process mining (OCPM) with stocha…
cs.LG2025
Integrating Human Knowledge Through Action Masking in Reinforcement Learning for Operations Research
Mirko Stappert, Bernhard Lutz, Niklas Goby +1
Reinforcement learning (RL) provides a powerful method to address problems in operations research. However, its real-world application often fails due to a lack of user acceptance…