Deep Reinforcement Learning for AGV Routing

In a Distribution Center (DC), walking from one location to another during the picking route can account for 60% to 70% of the operator’s working time. Reducing this walking time is the most effective way to increase overall productivity. In a previous series of articles, I have shared several methods using optimization strategies to reduce the walking distance of operators in your warehouse. These methods have limits when you have a large picking area. Therefore, automated solutions, using Automated Guided Vehicles (AGV) that brings the shelves directly to the operators, are now very popular. <a href="https://towardsdatascience.com/deep-reinforcement-learning-for-agv-routing-a9b9fe055304">Website</a>