Dynamic Lot Size Optimization with Reinforcement Learning
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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Dynamic Lot Size Optimization with Reinforcement Learning. / Voss, Thomas; Bode, Christopher; Heger, Jens.
Dynamics in Logistics : Proceedings of the 8th International Conference LDIC 2022, Bremen, Germany. ed. / Michael Freitag; Aseem Kinra; Hebert Kotzab; Nicole Megow. Cham : Springer Science and Business Media B.V., 2022. p. 376-385 (Lecture Notes in Logistics).Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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TY - CHAP
T1 - Dynamic Lot Size Optimization with Reinforcement Learning
AU - Voss, Thomas
AU - Bode, Christopher
AU - Heger, Jens
N1 - Conference code: 8
PY - 2022
Y1 - 2022
N2 - Production planning and control has a great influence on the economic efficiency and logistical performance of a company. In this context, this article gives an insight into the use of simulation as a virtual model of a filling machine in the process industry. Furthermore, it shows the possibilities of a reinforcement learning (RL) approach for dynamic lot sizing. The contribution indicates a possible implementation in an ERP system and shows how a decision support tool can support the planner to save up to 5% of costs compared to a human planner and a heuristic approach proposed by Groff.
AB - Production planning and control has a great influence on the economic efficiency and logistical performance of a company. In this context, this article gives an insight into the use of simulation as a virtual model of a filling machine in the process industry. Furthermore, it shows the possibilities of a reinforcement learning (RL) approach for dynamic lot sizing. The contribution indicates a possible implementation in an ERP system and shows how a decision support tool can support the planner to save up to 5% of costs compared to a human planner and a heuristic approach proposed by Groff.
KW - Lot sizing
KW - Reinforcement learning
KW - Simulation
KW - Engineering
UR - http://www.scopus.com/inward/record.url?scp=85129725752&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-05359-7_30
DO - 10.1007/978-3-031-05359-7_30
M3 - Article in conference proceedings
AN - SCOPUS:85129725752
SN - 978-3-031-05358-0
T3 - Lecture Notes in Logistics
SP - 376
EP - 385
BT - Dynamics in Logistics
A2 - Freitag, Michael
A2 - Kinra, Aseem
A2 - Kotzab, Hebert
A2 - Megow, Nicole
PB - Springer Science and Business Media B.V.
CY - Cham
T2 - International Conference on Dynamics in Logistics - LDIC 2022
Y2 - 23 February 2022 through 25 February 2022
ER -