Research On The Collaborative Delivery Method Of Trucks And Drones Based On Swarm Intelligence Algorithm

In the current climate,the logistics industry is facing unprecedented challenges.The single use of vehicles such as trucks for logistics distribution work is not only inefficient in terms of distribution,high transport costs and high carbon emissions that are harmful to the environment.In recent years,the field of drone logistics and distribution has developed rapidly,but the single use of drones for logistics distribution has certain limitations.Therefore,this paper proposes the idea of a logistics distribution system for trucks carrying drones.This paper aims to shorten the total distribution path length and distribution time to design a logistics distribution scheme for trucks carrying drones.In recent years,swarm intelligence algorithms have developed rapidly,and many novel algorithms have been proposed one after another.Compared with other swarm intelligence algorithms,the ant colony algorithm can better solve discrete problems and has a certain robustness,so this paper chooses the ant colony algorithm as the basic algorithm for solving the logistics distribution problem of trucks carrying drones.However,due to the shortcomings of the initialised pheromone matrix of the ACO,this paper also proposes to optimise and improve the ACO using the multi-headed pom-pom algorithm,using the prior knowledge obtained from the solution of the multi-headed pom-pom algorithm to enrich the initialised pheromone matrix of the ACO,and then refining the pheromone updating process.The improved ant colony algorithm still has room for improvement in terms of convergence speed,so the pheromone update formula of the hybrid algorithm is perturbed using the basic knowledge of physics-van der Waals force,which has a suitable function curve and acts as a perturbation term to fine-tune the pheromone update formula of the hybrid algorithm.The convergence speed of the hybrid algorithm is significantly improved with the addition of the van der Waals force perturbation term,and the overall robustness and scalability of the algorithm are also significantly improved.However,through the analysis of experimental results,it is found that the hybrid algorithm still has room for improvement in terms of accuracy after the van der Waals force optimization,so this paper talks about the core ideas of adaptive neighbourhood search algorithm such as destroy and repair to optimise the local search path of the hybrid algorithm,so that the hybrid algorithm has a greater chance of jumping out of the local optimal solution.The improved hybrid algorithm is then applied to the UAV traveller problem to design a new path planning scheme with the maximum weight of the UAV and the farthest flight distance as constraints,ultimately realising an integrated air-ground logistics interaction method.Finally,an experimental test of the official case using the optimised ant colony algorithm proves that the joint distribution scheme based on the UAV-traveller problem is efficient.