Dynamic Vehicle Routing Problem Under The Background Of The Traffic Big Data

With the rapid social progress and the rapid development of science and technology,the degree of traffic information is getting higher and higher.The application of large traffic data in traffic management system will be the key factor to solve the problem of urban traffic congestion.Cargo transportation is one of the important production activities of mankind and supports the development of other economic activities.At present,the freight costs of each country account for about 15%of its gross domestic product.In order to save resources,improve the efficiency of freight systems and reduce freight costs,countries began to optimize the freight system.The freight system is a complex system that contains multiple objects,multiple resources,and many optimization problems.These issues can be divided into three levels from their long-term impact:strategic level,tactical level,and operational level.Regardless of any level of the problem can be optimized for the entire freight system has a significant significance.This paper focuses on the study of a problem at the operational level-the dynamic deterministic vehicle routing problem based on real-time traffic information to explore the optimization method of freight system.The vehicle path problem is one of the fastest growing areas in more than 40 years.With the development of communication and information technology,customers need manufacturers and service providers to meet their needs in real time.Therefore,the research of vehicle routing problem is mainly to solve the problem of static problem to solve the dynamic problem.In order to maximize the scale of logistics enterprises to achieve,while the logistics and distribution in the city road network fast and safe transfer.Based on the real-time traffic information shared by the large data platform,this paper solves the open-loop VRP problem,which is based on the real-time traffic information shared by the large data platform,and realizes the real-time updating of the customer's demand,the distribution center and the soft-time window shared by the vehicle.More quickly and accurately solve such problems.