Research On Optimization Of Distribution Vehicle Scheduling In DB Company

With the development of the social economy,Logistics has played an increasingly important role in economic activities and has gradually received people’s attention.In the logistics system,distribution directly contacts consumers,and its service quality will directly affect customers’ satisfaction with logistics service.As an important part of distribution,vehicle scheduling involves a wide range and has many influencing factors,so it is the key to the optimization of logistics distribution.Reasonable optimization of vehicle scheduling has a very important impact on the service level,efficiency and cost of the whole logistics system.DB Company is a third-party logistics enterprise.At present,it uses people to arrange vehicle scheduling.The dispatcher is responsible for the arrangement of vehicle dispatching tasks,and the driver is responsible for the planning of delivery routes on the way.This vehicle scheduling method mainly depends on manual labor,which leads to low loading rate and delivery timeout.Based on the above background,this thesis studies the vehicle scheduling of DB Company as follows:(1)This thesis combines the classification of vehicle scheduling problems and related solving algorithms.First,the classification and solution algorithm of vehicle scheduling problems are introduced.Then,compare various algorithms for solving the problem and select a genetic algorithm with fast convergence speed and high quality as the solving algorithm of this thesis.(2)This thesis analyzes and models the vehicle scheduling problem of DB Company.Firstly,the main problems in vehicle scheduling in DB Company are analyzed,and then a multi-vehicle and multiple target scheduling model with time windows is established according to the factors affecting vehicle scheduling.(3)This thesis designs a solution algorithm for the model and analyzes the results.Due to the poor local search ability of genetic algorithm,this thesis adds the idea of large-scale domain search algorithm to the genetic algorithm to enhance the local search ability of genetic algorithm,and realizes the algorithm function through MatlabR2020b.Finally,the optimization scheme is compared with the actual scheme from four aspects:delivery cost,timely delivery rate,loading rate and other effects,which proves the algorithm designed in this paper is effective for vehicle scheduling optimization.In this thesis,the vehicle scheduling problem of DB Company is solved by establishing the model and designing the algorithm,which has certain practical significance.The results show that compared with the actual solution,the optimized solution saves 2030.48 kilometers in mileage,distribution costs decreased by 7.34%,increases the average loading rate by 1.33%,and increases the delivery time rate by 12.30%.,the objective function value decreased by 10.90%.In a word,the optimized scheme improves the distribution efficiency and reduces the distribution cost.