Online preference learning for adaptive dispatching of AGVs in an automated container terminal
AGV dispatching can be done by using a policy recommending the best job assignment. The policy proposed in this paper is based on a pairwise preference function. The policy can be adapted by having the preference function updated through learning. The pairwise preference function is implemented as a neural network.
automated container terminal vehicle dispatching machine learning genetic algorithm artificial neural network