Deep Reinforcement Learning-Driven Scheduling in Multijob Serial Lines: A Case Study in Automotive Parts Assembly.
Sanghoon LeeJinyoung KimGwangjin WiYuchang WonYongsoon EunKyung-Joon ParkPublished in: IEEE Trans. Ind. Informatics (2024)
Keyphrases
- reinforcement learning
- mixed model assembly
- function approximation
- case study
- manufacturing cell
- scheduling problem
- data driven
- reinforcement learning algorithms
- line drawings
- learning algorithm
- straight line
- optimal policy
- optimal control
- round robin
- machine learning
- hough transform
- multi agent
- automotive industry
- dynamic scheduling
- production system
- spatial relations
- scheduling algorithm
- d objects
- reinforcement learning methods
- dynamic programming
- temporal difference
- resource constraints
- supervised learning
- markov decision processes
- line segments
- resource allocation
- quality of service