Entwicklung einer KI-basierten Reihenfolgestrategie für Hochregallager mit autonomen Fahrzeugen

Abstract

Using Artificial Intelligence (AI) in particular machine learning algorithms to solve problems in practice and research is widespread and established in several areas. However, there is still a research gap in the formation of storage strategies in high-bay warehouses with autonomous vehicles (AVS/RS). One of the AI methods that has recently attracted attention is Reinforcement Learning (RL), which includes deep learning. This paper presents how deep reinforcement learning can be used to develop a sequencing policy for AVS/RS.