The invention belongs to the technical field of logistics distribution, and particularly relates to an unmanned aerial vehicle and
truck collaborative
distribution method based on multi-target
reinforcement learning, and the method comprises the steps: order clustering: a logistics
service provider carries out the clustering of orders according to a K-means method, enables the orders with the
similar distribution time and address to be divided into one order cluster, and carries out the clustering of the orders according to a K-means method; the unmanned aerial vehicles are delivered by the
truck and the unmanned aerial vehicles carried by the
truck; according to the NSGA-II
algorithm, multiple targets such as
path cost, distribution time and carbon emission are considered, and optimal paths of multiple schemes are provided; and planning an optimal path by adopting a
reinforcement learning method. According to the cooperative logistics
distribution method based on the unmanned aerial vehicle and the truck, the three targets of logistics distribution time, cost and carbon emission are considered, the dynamic conditions of low-altitude traffic restriction of the unmanned aerial vehicle, the
road congestion condition of the truck, load constraint and the like are also considered, the optimal path is optimized by adopting a
reinforcement learning mode, and the logistics distribution efficiency is improved. And parameter setting of reinforcement learning is automatically updated by using a non-dominated
sorting algorithm, so that multi-dimensional optimal path selection can be provided for logistics service providers.