Deep reinforcement learning‐based balancing and sequencing approach for mixed model assembly lines

Deep reinforcement learning‐based balancing and sequencing approach for mixed model assembly lines

Abstract A multi‐agent iterative optimisation method based on deep reinforcement learning is proposed for the balancing and sequencing problem in mixed model assembly lines. Based on the Markov decision process model for balancing and sequencing, a balancing agent using a deep deterministic policy g...

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Bibliographic Details
Main Authors: Youlong Lv, Yuanliang Tan, Ray Zhong, Peng Zhang, Junliang Wang, Jie Zhang
Format: Article
Language:English
Published: Wiley 2022-09-01
Series:IET Collaborative Intelligent Manufacturing
Subjects:
assembling
control engineering computing
genetic algorithms
gradient methods
iterative methods
learning (artificial intelligence)
Online Access:https://doi.org/10.1049/cim2.12061

Internet

https://doi.org/10.1049/cim2.12061

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