Simulation Study On The Combined Logistics Delivery Path Of Unmanned Aerial Vehicles And Vehicles

With the rapid development of the economy,the increase in logistics demand and orders has brought great pressure to logistics delivery.Delivery delays often occur during the logistics delivery process,and delivery costs are also increasing year by year.Delivery plays an increasingly important role in the entire logistics system.With the development of technology,drones have started to be applied in logistics distribution,which is beneficial for reducing urban congestion.In order to alleviate the problem of short battery life during drone delivery,a delivery mode has emerged where drones can be charged and loaded on vehicles.The issue of whether the distribution path is reasonable in logistics distribution directly affects the cost and speed of distribution.Therefore,choosing the correct distribution path can improve service quality,reduce distribution costs,and increase customer satisfaction with logistics distribution.This article first discusses relevant research on vehicle routing problems.This article provides a detailed introduction to the traditional vehicle problem of considering vehicle delivery and pickup as a whole(VRPSDP)in the transportation process,reducing vehicle transportation distance,providing services to customer points,and improving the interests of the enterprise.Then,a brief overview of the collaborative delivery mode between drones and vehicles is provided.When considering the issue of collaborative delivery between vehicles and drones,only the issue of vehicle delivery is considered,without considering the issue of vehicles delivering and picking up goods simultaneously,thus increasing costs.Therefore,this article adds the issue of vehicle pickup in the process of vehicle and drone delivery.This article establishes the VRPSPDTW-D model to solve the vehicle routing problem with the lowest total delivery cost.The total delivery cost mainly considers startup cost,time window waiting cost,delivery cost,and carbon emission cost.The adaptive large neighborhood search algorithm(ALNS)is used to solve the optimal path.At the same time,the adaptive large neighborhood search algorithm(ALNS)and Tabu search algorithm are combined to solve the optimal path.The two solutions are compared and analyzed to prove that the ALNS+TS hybrid algorithm is superior to the ALNS algorithm in terms of total cost and iteration speed.Finally,simulation experiments were conducted using the C101 example in the Solomon dataset,and the total cost of solving the optimal path using the ALNS algorithm was 885.34 yuan,while the total cost of solving the optimal path using the ALNS+TS algorithm was 866.55 yuan.At the same time,in terms of iteration time,the ALNS algorithm reached a plateau in 10 minutes,while the ALNS+TS hybrid algorithm reached a plateau in 7 minutes.The effectiveness and rationality of the model and algorithm improvements were verified from the above two aspects.