Web: http://arxiv.org/abs/2205.03294

May 9, 2022, 1:11 a.m. | Lucain Pouget, Timo Hasenbichler, Jakob Auer, Klaus Lichtenegger, Andreas Windisch

cs.LG updates on arXiv.org arxiv.org

We investigate the feasibility of deploying Deep-Q based deep reinforcement
learning agents to job-shop scheduling problems in the context of modular
production facilities, using discrete event simulations for the environment.
These environments are comprised of a source and sink for the parts to be
processed, as well as (several) workstations. The agents are trained to
schedule automated guided vehicles to transport the parts back and forth
between those stations in an optimal fashion. Starting from a very simplistic
setup, we …

arxiv context deep learning management production q-learning

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