Research On Multi-objective Optimization Of Joint Delivery Path Of Trucks And UAVs

With the continuous development of information technology,e-commerce has gradually become one of the key development industries in China.However,the “last mile” of e-commerce logistics is faced with high logistics costs,customer satisfaction and other problems,and logistics problems have become a major obstacle to the development of e-commerce.In recent years,the emergence of UAVs has provided a new distribution mode for logistics distribution.However,due to the features of UAVs,it is restricted in terms of load and flight mileage.Therefore,this thesis studies the joint delivery of trucks and UAVs considering carbon emissions and regional constraints,provides a new solution to solve the problem of e-commerce logistics and distribution.This thesis firstly analyzes the research status at home and abroad of vehicle routing problem,UAV distribution,and joint distribution of trucks and UAVs.The related theories of logistics distribution,vehicle routing problem of multi-objective decision-making and joint distribution of trucks and UAVs are expounded.Secondly,the customer satisfaction expression function is given,and the cost composition and regional constraints are analyzed,and an optimization model for the joint distribution path of trucks and UAVs is established that considers carbon emissions and regional constraints.The weight coefficient of each objective is calculated by the ranking entropy weight method.Thirdly,improved ant colony algorithm.The idea of dynamic classification of artificial bee colony algorithm is introduced,the ant colony is divided into two ant states,and different local pheromone update strategies are implemented respectively.In order to maintain the diversity of the population,high-quality solutions are exchanged and the upper and lower limits of pheromone concentration are limited.Finally,an example is used to prove the constructed optimal model for the joint distribution of trucks and UAVs considering carbon emissions and regional restrictions,as well as the improved ant colony algorithm.The calculated results are compared with the results of ant colony algorithm to verify the superiority of the model and algorithm in this thesis.