Reinforcement Learning for Two-Stage Permutation Flow Shop Scheduling—A Real-World Application in Household Appliance Production

Reinforcement Learning for Two-Stage Permutation Flow Shop Scheduling—A Real-World Application in Household Appliance Production

Solving production scheduling problems is a difficult and indispensable task for manufacturers with a push-oriented planning approach. In this study, we tackle a novel production scheduling problem from a household appliance production at the company Miele & Cie. KG, namely a two-stage pe...

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Bibliographic Details
Main Authors: Arthur Muller, Felix Grumbach, Fiona Kattenstroth
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Reinforcement learning
production scheduling
permutation flow shop scheduling problem
Online Access:https://ieeexplore.ieee.org/document/10401920/

Internet

https://ieeexplore.ieee.org/document/10401920/

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