Application Research On The Fruits And Vegetables Distribution Route In Baohe Distrist Of Hefei City Based On Ant Colony Algorithm

Route planning must be considered in vehicle transport. The implementation of the route planning is not only the process of creating economic benefits, but also the process of creating efficiency. With the development of economic integration, the scope of transportation are becoming more and more widely and the transportation environment are also becoming increasingly complex, which represents higher requirements and necessities for vehicle route optimization works. In order to make social materials meet the social stable demand, the geographical scope of transportation, the number of personnel requirements, and the time and cost needed for transportation, the coordination problem and many other factors are all need to be considered in transportation route optimization. Under the influence of such multiple factors, transportation route optimization has become a difficulty in transportation studies, and how to plan reasonable and viable transportation routes effectively is the key problem to improve transportation management efficiency.This article mainly goes around with ant colony algorithm in the research and application in the choice of the vehicle transport route. Based on the summary of the existing routing optimization researches, the characteristics of the existing route optimization models has been analyzed, a kind of suitable transportation route optimization model has been established, which provides a new way to solve the problems of transportation route optimization. First of all, this paper analyzes the purpose and significance of the research and application of ant colony algorithm in vehicle transport route optimization, demonstrates the necessities of this research, shows the research status of transport route selection at home and abroad and explains the contribution of this article. Secondly, the paper expounds the correlation theories of vehicle route optimization methods and the characteristics of ant colony algorithm in the route optimization. And latterly analyzes of route optimization problems, and put forward the strategies or solutions to solve the problems. Finally, To the fruit and vegetable logistics distribution in BaoHe District of HeFei City as an example, the transportation route optimization model has been established. According to the feature of ant colony which can quickly find the shortest path among the route selections, a kind of transportation route optimization model based on improved ant colony algorithm has been putted forward. One of the importance part of this chapter is the simulation in the MATLAB, which analyzes its convergence, verifies the feasibility and reliability of the model through simulation, and also proves the validity and practicability of the transportation route optimization model based on improved ant colony algorithm.