Study On The Route Of Express Vehicle Based On Urban Road Network

Since the 21st century,the Internet industry has grown rapidly.We have already entered the era of e-commerce.Online shopping has now become the most popular consumption method in the contemporary era,and a new industry that has emerged with it is the logistics service industry.Data shows that in 2014,China's express delivery business revenue reached 294 billion yuan,a year-on-year increase of 42%,and the total number of express delivery services reached 14 billion,an increase of 52%year-on-year,which surpassed the United States in the world.In 2015,China's express delivery revenue reached 265 billion yuan,an increase of 30%year-on-year,and 19.6 billion in express delivery volume,an increase of 40%year-on-year.By 2016,China's express delivery volume broke through 30 billion items for the first time,reaching 31.28 billion pieces,a year-on-year increase of 51.4%.However,with the rapid increase in express delivery volume,the operating costs of the express delivery industry implied in it have also continued to rise.The main processes of the express transportation industry include cargo assembly,item transportation,sorting operation of transfer stations,and final delivery of dispatch points.Each courier company uses more advanced logistics technology to reduce costs in the first three parts,but so far,the final courier delivery is carried out by means of manual delivery.Therefore,it is of great significance to study the express delivery vehicle route optimization problem to improve the delivery chain operation efficiency of the express delivery industry,save the delivery costs,and enhance the express company's own industry competitiveness.This article first briefly describes the overall research background and research ideas,and expounds the purpose and significance of the research.At the same time,this article introduces the concept of express delivery business at home and abroad,the problem of vehicle routing and the research status of ant colony algorithm and the problems in current research.Second,a series of common optimization methods for solving vehicle routing problems are introduced.Thirdly,based on the characteristics of urban express delivery and distribution,based on relevant information in urban road network,taking into account uncertain time factors and introducing time penalty coefficients,a multi-objective,time-window-integrated vehicle path is constructed.model.Then,this paper uses the improved maximum and minimum ant colony algorithm to optimize the model.The traditional basic ant colony algorithm has extremely slow convergence rate,and the obtained solution tends to converge to local optimality.Since the initial search stage lacks sufficient pheromone,it usually takes a long time to find a feasible solution,and it is very easy to solve.Stagnation occurs at a certain stage.That is,all ants may find the same solution in the search process,and then solve the problem and cannot search for a better solution.Therefore,we use the maximum and minimum ant colony algorithm to optimize the traditional ant colony algorithm to solve the problem model.The maximum and minimum ant colony algorithm emphasizes the development of the optimal path,and sets the upper and lower limits of the value of the pheromone,keeping the pheromone between maximum and minimum.At the beginning of the maximum/minimum ant colony algorithm,it is usually set that the pheromone is the maximum value in the selected value interval,so that more possible paths can be quickly and correctly searched during the initial search.At the same time,the maximum and minimum ant colony algorithm can also re-initialize the pheromone in the process of searching for an optimal solution to avoid finding the local optimal value.Because the vehicle path model in this paper takes into account the uncertain time influencing factors and the time penalty coefficient,the maximum and minimum ant colony algorithm will be improved correspondingly.In this paper,in the original path construction of the maximum and minimum ant colony algorithm,the optimality of the time window factor is considered,and the traffic time penalty coefficient is added,a new solution model path is constructed,and corresponding rules are also introduced in the pheromone update rule.The parameters and the comparison of the experimental data with the common ant colony algorithm show that the improved maximum-minimization ant colony algorithm is relatively good both in the solution speed of the objective function and the optimality of the solution,and the improvement is verified.The effective feasibility of the algorithm.In the end,this paper studies the distribution of some express delivery companies and relevant information data in Yangzhou.Through the analysis of the results,we can give the express company some reasonable suggestions to reducing its operating costs,which is of far-reaching significance to the company.