  The application of drones in the last-mile distribution is a research hotspot
in recent years. Different from the previous urban distribution mode that
depends on trucks, this paper proposes a novel package pick-up and delivery
mode and system in which multiple drones collaborate with automatic devices.
The proposed mode uses free areas on the top of residential buildings to set
automatic devices as delivery and pick-up points of packages, and employs
drones to transport packages between buildings and depots. Integrated
scheduling problem of package drop-pickup considering m-drone, m-depot,
m-customer is crucial for the system. We propose a simulated-annealing-based
two-phase optimization approach (SATO) to solve this problem. In the first
phase, tasks are allocated to depots for serving, such that the initial problem
is decomposed into multiple single depot scheduling problems with m-drone. In
the second phase, considering the drone capability constraints and task demand
constraints, we generate the route planning scheme for drones in each depot.
Concurrently, an improved variable neighborhood descent algorithm (IVND) is
designed in the first phase to reallocate tasks, and a local search algorithm
(LS) are proposed to search the high-quality solution in the second phase.
Finally, extensive experiments and comparative studies are conducted to test
the effectiveness of the proposed approach. Experiments indicate that the
proposed SATO-IVND can reduce the cost by more than 14% in a reasonable time
compared with several other peer algorithms.
