Truck-drone collaborative distribution and pickup route optimization
Addressing the problem of truck-drone collaborative distribution and pickup route optimization,considers the maximum carrying capacity and endurance of drones to minimize distribution and pickup costs and time.A model is constructed for a single truck carrying multiple drones for distribution and pickup,and a phased iterative optimization algorithm is designed.In the first phase,threshold screening and the K-means++clustering algorithm are used to cluster customer points and determine the delivery points for the truck.In the second phase,an exhaustive method is used to determine the truck's distribution and pickup route.In the third phase,a neighborhood search algorithm is employed to optimize the drones'distribution and pickup routes.The total time and cost for truck-drone collaborative distribution and pickup under different numbers of clustering centers K are calculated and compared to determine the optimal distribution and pickup route.The results show that when K=3,the total time and cost for truck-drone collaborative distribution and pickup are minimized.Compared to using only a truck for distribution and pickup,the total time is reduced by 75.98％,and the total cost is decreased by 12.34％.Employing truck-drone collaborative distribution and pickup in the optimized area can reduce distribution and pickup costs and improve last-mile distribution and pickup efficiency.
distribution and pickup routetruckdroneoptimization algorithm
万方数据
维普
