Consultants at HHLA subsidiary HPC Hamburg Port Consulting are preparing a quantum leap in the organisation of terminal processes: Artificial Intelligence (AI) that stacks containers and finds the best solution independently. Self-learning “agents” are programmed to assign containers to the ideal storage space.
At first glance, the task of optimally stacking these many coloured boxes looks easy to solve. But there is actually a large number of possible storage places for each container. Could “reinforcement learning” maybe help here? In this most modern variation of artificial intelligence (AI) the AI module doesn’t blindly pursue a predetermined target. Programmed “agents” move in a virtual training environment and improve themselves using a reward function.
Thus far, the reinforcement learning principle could be implemented in a model version. HPC got the virtual logistics agent to stack 800 containers in 100 stacks. They learned to choose storage spaces in such a way that the number of times a container has to be moved between entry and exit is minimised. For the next step in the project, the learning agents will work in scenarios that correspond to the real conditions in a container terminal.