Research On Time-dependent Vehicle Routing Problem Based On Dynamic Demand

With the development of science and technology and the improvement of living standards,people’s requirements for logistics and distribution services are gradually increasing.In the distribution process,logistics companies not only need to consider the distribution services of existing customers,but also need to consider real-time new customer needs and complex urban traffic conditions.The logistics distribution path planning is more complicated.Therefore,it has become a real need to study the problem of vehicle route planning considering dynamic demand and urban traffic conditions.On the basis of research on relevant domestic and foreign research results,through the analysis of the distribution business of S company,considering the dynamic new customer needs and changing traffic conditions,this article focuses on single-car parking,multi-vehicle,and dynamic vehicle delivery with soft time windows.The path problem was studied.Firstly,it analyzes the processing of dynamic demand and the travel time of vehicles,and takes the minimum delivery cost as the objective function,and establishes the time-dependent vehicle routing problem model of S company with dynamic demand.For dynamic new customer needs,virtual customer points are introduced to distinguish between customers that have been served and customers to be served,and a regular update strategy is used to process dynamic customer information;for urban traffic conditions,the time-dependent travel speed function is used to describe it.Secondly,a two-stage algorithm is designed to solve the problem model of S company.In the initial route construction stage,an improved genetic algorithm is used to solve the initial distribution plan.In the route update stage,the lowest cost insertion algorithm is used to insert dynamic customer needs to make partial adjustments to the route.Finally,using the distribution business of Weifang S Company as an example,the data is substituted into the model,and the improved genetic algorithm designed is used to obtain the initial stage path plan;taking real-time dynamic information into consideration,the insertion algorithm is used to insert new customer needs.The initial path obtained by the stage improvement genetic algorithm is adjusted to obtain the distribution plan of the dynamic update stage;then,the distribution plan is compared with the initial stage distribution plan,and the distribution cost and delivery time of the dynamic update plan increase.Although the delivery cost and delivery time are sacrificed,if dynamic factors are not taken into account,the delivery will be less profitable by 480 yuan,and the average vehicle loading rate has also increased by 9.83%.It can be seen that dynamic customer demand and traffic conditions have an impact on logistics delivery.After comparing the two-stage algorithm in this paper with the genetic algorithm,the results show that although the solution time of the two-stage algorithm in this paper is longer than that of the genetic algorithm,the distribution cost solved by the algorithm in this paper is 26.78 lower than that of the genetic algorithm.Yuan,the delivery time has been reduced by 5.78 minutes.Therefore,the validity of the model and algorithm in this paper is verified,and it provides guidance for the distribution activities of S company,which has certain practical value.