Dynamische Losgrößenoptimierung mit bestärkendem Lernen

Research output: Journal contributionsJournal articlesResearchpeer-review

Authors

Production planning and control has a great influence on the economic efficiency and logistical performance of a company. In this context, the 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 associated possibility 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 % costs.

Translated title of the contributionDynamic Adjustment of Lot Sizes with Reinforcement Learning
Original languageGerman
JournalZWF Zeitschrift fuer Wirtschaftlichen Fabrikbetrieb
Volume116
Issue number11
Pages (from-to)815-819
Number of pages5
ISSN0947-0085
DOIs
Publication statusPublished - 2021

    Research areas

  • Engineering - Reinforcement Learning, Simulation, lot sizing, dynamic adjusment

DOI