The invention relates to the field of intelligent logistics optimization, and discloses an unmanned aerial
vehicle transportation route distribution method for logistics multi-point transportation, which comprises the following steps: carrying out coordinate-weight joint
standardization on a distribution
point set to generate a three-dimensional
feature vector; constructing a topological complex based on the standardized data, and extracting a key ring structure through continuous coherence; encoding the ring structure into a topological constraint term of a
quantum model, and constructing Hamiltonian containing distance, load and topological constraint; dividing
quantum sub-blocks according to the topological ring, and executing block annealing solution through chain
coupling constraint; and carrying out topology-guided privacy
fine tuning under a
federated learning framework by using gradient information of a
quantum solution. According to the method, a complex path
optimization problem is decomposed into sub-problems capable of being processed in parallel through a quantum topological coding and block annealing strategy, quantum bit grouping is guided through a topological ring structure, the calculation complexity is reduced, efficient solving of a large-scale logistics network is achieved, and the calculation speed is increased compared with a traditional optimization method.