A Study On Vehicle Routing Optimization Model Based On DVRP In Pick-up Scenario

In recent years,the sales mode of e-commerce has been developing,compared with the traditional sales mode,it requires real-time response to online orders,so the requirement of logistics transportation efficiency is constantly improving.Because of the huge investment in infrastructure construction,it is difficult to change and optimize the long-distance cross-regional logistics transportation path in a short time,so the emphasis of improving logistics transportation efficiency falls on the two terminal links of collecting goods and distributing goods,and these two links have the highest contact frequency with customers and the strongest customer perception.If the vehicle route of these two links can be reasonably and effectively planned,it can greatly improve efficiency,increase customer satisfaction and bring economic benefits to distribution enterprises.The solution of this kind of problem can be abstracted as the vehicle routing problem,which is one of the most important economic problems in the field of combination optimization,and its application scenarios are various,such as express delivery scene,take-out meal delivery scene,taxi call service and so on.As far as the collection scenario is concerned,today's customer demand is characterized by small batch and large quantity,and the number of customers has increased sharply compared with the past.And the real-time processing of orders means that logistics enterprises cannot know all customer demand information in the initial path planning stage,so the traditional VRP model based on static demand hypothesis is difficult to provide guidance for the collection route planning of logistics enterprises today.Therefore,Dynamic Vehicle Routing Problems model(DVRP)based on the dynamic demand hypothesis is established in this paper and the solution strategy and method of the model are designed..This paper starts from the field of VRP research,deeply understands and compares the existing domestic and foreign literature research scene,modeling method,solution method and so on,analyzes and compares the research results and shortcomings.Based on the traditional static demand VRP model,the DVRP model considering dynamic demand is constructed and time dependence and demand dynamics of the speed in the model are processed,the relevant parameters are set up,and the DVRP mathematical model is established and analyzed.In this paper,the solution of the DVRP model is transformed into the solution of Time Dependent Vehicle Routing Problem(TDVRP)and Heterogeneous Fleet Open Vehicle Routing Problems(FOVRP)and the solution algorithm is designed.In order to solve the problem that the traditional greedy algorithm is not of high quality,this paper adopts the Held Karp model to improve the traditional greedy algorithm,and uses it to produce the initial solution.Then the taboo search algorithm is used to optimize thesolution.Nine kinds of neighborhood moving methods and fitness function which can evaluate the unfeasible solution are designed,increasing the diversity of neighborhood and improving the search ability of the algorithm.The designed algorithm mentioned above is used to solve the Solomon examples and the Breedam examples to verify the effect of the algorithm improvement and the effectiveness of the algorithm solution.In addition,based on Solomon example,the DVRP example is designed and solved by the algorithm designed in this paper for future scholars to compare the results.Compared with the static demand VRP model,the DVRP model established in this paper is more in line with the actual situation.In the processing of customer demand,the strategy of transforming dynamic demand into static demand is proposed,which is easy to understand and adapts to the high dynamics of demand.Regarding solving algorithm,the algorithm designed in this paper is simple and effective,and the search ability is strong.It can provide guidance for the vehicle route optimization of logistics enterprises under the cargo collection scenario,help them reduce the driving distance of vehicles and improve the efficiency of logistics distribution on the basis of meeting the needs of customers,and bring economic benefits to enterprises.