Based On Optimization Of Travel Time Prediction Logistics Transport Vehicles Route Optimization Study

Now in today’s rapid economic development of society, logistics has become an important cornerstone of society’s rapid economic takeoff. In the fifteenth year of the plan, the development of the logistics industry, put on the national strategic level, the policy statement of the logistics industry in the spring came. Throughout the development of the logistics industry, so far, two major problems plaguing numerous logistics people, but also to produce a core source of logistics costs, namely transport costs and warehousing costs. According to the survey data on the relevant international authorities show that China’s logistics industry, transportation costs accounted for more than 50% of the total cost of logistics, accounting for 20% to 30% of GDP. This huge figure means that every year, the proportion of the astronomical sum of money wasted, so the study of transport costs on the very necessary.Domestic and foreign scholars in the process of logistics and distribution vehicle routing problem have made a very large, very large, very broad research and discussions have come to a lot of very good results. However, the general determined that the vehicle travel time between customers and distribution centers, mainly through the geographical coordinates of customer acquisition and distribution centers, the use of a linear equation and the average speed of the vehicle manufacturers to calculate the distance between the coordinates of the points, and did not take into account the reality in complex traffic situations, when the vehicle routing scheme drawn encounter traffic jams and other complex situations, you can’t very well get the desired results according to the plan.Based on a detailed study of multi-model vehicle routing problem with time windows on the car to find a method of travel time between the realistic traffic conditions of customers and distribution centers out a way to solve that by driving traffic flow guidance technology members of behavioral characteristics, as well as travel time prediction Dijkstra shortest path algorithm, the average traffic flow data acquisition use surveys to predict and find the vehicle travel time between customers and distribution centers, providing vehicle travel time data to support the follow-up vehicle Routing optimization. In the algorithm is designed to solve the model, based on the concept of a two-stage algorithm, combined with driver behavior characteristics, travel time prediction, Dijkstra shortest path algorithm and simulated annealing algorithm for solving the Vehicle Routing solutions to meet the requirements.In this paper, the specific contents include:Firstly, the paper title background and research status at home and abroad, and the topic of meaning and purpose of this paper describes the innovation. Secondly, the vehicle routing problem and the traffic flow guidance theories in detail. Finally, the establishment of a multi-car vehicle routing problem with time window model, based on the concept of two-stage algorithm design, and the use of computer simulation software programming applications through case drawn vehicle routing solutions to meet the requirements.