Research on Path Planning for Rural Truck-Drone Combined Delivery

In order to solve the truck and drone cooperative distribution path planning problem that simultaneously picks up and delivers goods and reduces carbon emissions, this paper establishes a joint path planning model considering carbon emissions by taking the minimisation of the total transport cost as the goal and combining the constraints of load and range. The model is solved by designing an improved genetic algorithm and compared with the PSO algorithm to verify the effectiveness of the model and algorithm. The results show that the model can significantly reduce the logistics cost, especially in the medium-sized case, the cost reduction reaches 52.1%. The improved genetic algorithm outperforms PSO in terms of path planning, convergence performance and cooperative logic, and can effectively shorten the distance travelled by trucks by 36.2%- 52.9%, and achieve the complementary advantages of trucks and drones. The model and algorithm have good adaptability in different scale rural e-commerce logistics scenarios, which provides theoretical support for cost reduction and efficiency.