Research On Joint Distribution Routing Problem Of Vehicle And Drone

In the field of logistics and distribution,as a new type of transportation vehicle,drones have many advantages 'such as' low cost and immunity to the influence of ground traffic congestion during flight.However,drones are inferior to traditional transportation vehicles such as trucks in terms of flight distance and load capacity.To meet the distribution needs of various customers,the use of both drones and trucks to complete logistics distribution tasks is increasingly favored by the industry.Such as urban and rural logistics and goods distribution,drug distribution and other emergency application has the model species.This mode helps to greatly reduce the overall logistics distribution cost by the task assignment and cooperation of the two vehicles,but brings great difficulty to logistics scheduling.It is a new problem different from the traditional vehicle routing problem.The traditional vehicle routing problem is only planned for the path of the vehicle,and the joint distribution problem of vehicles and drones is to schedule and arrange the paths of vehicles and drones at the same time.The two distribution vehicles have their own advantages and disadvantages.Its reasonable combination is the key to improve the distribution efficiency and reduce the distribution cost,especially in this paper,the reality of the drone needs to take off and land at multiple stations,the complexity of the problem is much higher than that of traditional vehicles that only use vehicles for distribution path problem.In response to this problem,on the basis of a clear definition of it,a mixed integer programming model was established,which was designed according to the collaborative characteristics of vehicles and drones and the relationship between vehicles and drones and different customer points(Adaptive Large Neighborhood Search,ALNS)algorithm,according to the characteristics of the problem,the corresponding initialization,deletion and insertion operators in the algorithm are improved,and the design of the key links of the algorithm is elaborated in detail.In the experiment,the results of ALNS algorithm and Gurobi calculation are compared and analyzed.In the analysis of the experimental results,the distribution costs of vehicles and drones and the number of customer service points were analyzed,and the vehicle and drone joint distribution mode was compared with the truck-only distribution mode.The sensitivity analysis of the maximum mileage and the ratio of drone to truck speed is carried out,and finally the solution of an application example is shown based on the electronic map.The research results show that the results obtained by the ALNS algorithm are the same as those of Gurobi or even better under a certain calculation time limit,which has a clear advantage over Gurobi in running time,and reflects the effectiveness of the ALNS algorithm.The joint distribution model of vehicles and drones greatly saves the overall distribution cost,which verifies the effectiveness of the joint distribution model of vehicles and drones.For enterprise decision makers,establishing drone stations in rural and mountainous areas with underdeveloped transportation or blocked by waterways and mountain roads to achieve coverage of surrounding customers can better leverage the advantages of drone distribution and greatly save the overall Delivery cost.