AI research on reinforcement learning
Science Prize Logistics 2024 awarded
The Science Award Logistics 2024 goes to Junior Professor Dr.-Ing. Sebastian Lang: Following a presentation by the four finalists at the BVL Supply Chain CX in Berlin on Wednesday, the jury selected his work as the winner. The award ceremony took place on Thursday, also as part of the event. The award is endowed with 5,000 euros and is sponsored this year by Hellmann Worldwide Logistics.
In his dissertation, Sebastian Lang examines an important area of artificial intelligence with regard to the calculation of production schedules. He uses methods of reinforcement learning (RL). This makes it possible to train software using trial-and-error so that it can then calculate production process decisions in real time.
RL applications: Particularly suitable for demanding sequence planning
The difference to established procedures is that training is not based on training labels, but on trial and error. In the long term, RL applications draw the right conclusions from the feedback and develop the right planning and control strategy step by step. Reinforcement learning is particularly suitable for very demanding scheduling in highly volatile, complex or fault-prone production environments.
The concrete result of Sebastian Lang's dissertation is a process model for developing, integrating and applying reinforcement learning methods for production process planning. Sebastian Lang's application was suggested by his doctoral supervisor, Prof. Dr.-Ing. habil. Michael Schenk (formerly Otto von Guericke University Magdeburg).
On behalf of the jury, Prof. Dr. Dr. h. c. Wolfgang Kersten said: "Sebastian Lang's special scientific achievement is also underlined by the fact that his research results have already been published extensively. The real-life applications he investigated also illustrate the enormous practical relevance of his research. The jury was also impressed by the fact that the prizewinner was able to explain the highly complex scientific contexts of his dissertation in a way that is easy for practitioners to understand."
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