Reinforcement Learning in the Warehousing Industry

Artificial Intelligence and Machine Learning is advancing at an ever-increasing rate. Reinforcement Learning (RL) is one area of Machine Learning which is proving to be incredibly promising for the future of business efficiency and optimisation. Within the Warehousing and Logistics industry, there are some unique challenges, some of which can be addressed and improved with the application of Reinforcement Learning. One of these examples is the Picking and Putaway strategies which are implemented within modern Warehouse Management systems. If a Reinforcement Learning algorithm were to be developed to address this scenario, the benefits to businesses would improve efficiency and profitability. However, Reinforcement Learning has some nuanced difficulties which will need to be handled when scaling a solution like this to a production-ready environment.