The Research Of Vehicle Routing Problem Based On Improved Ant Colony Algorithm For Vegetables Logistics Distribution

China is a country based on the agriculture, few people study on agricultural logistics. Vegetable industry is a promising industry among agriculture. With the rapid economic development, the pace of life speeds up, the continuous improvement of people's living standards and better quality of life for the pursuit. Vegetable consumption distribution become the objective needs of urban residents, a large number of vegetable distribution centers have emerged. Among distribution business there are many optimizing strategies. The vehicle scheduling problem has great effect on improving distribution speed, quality of service and economy benefit.Ant colony algorithm was a random searching method, which simulated the behavior of ant in nature. Its main characteristics are stronger robustness, eximious distributed computation mechanism and apt combined with other approaches. but it has the limitation of stagnation, and is easy to fall into local optimums.The contents of the research as the following:(1)By analyzing the situation of China logistics, the conclusion was reached that Optimizing vehicle scheduling can decreases Business costs.(2) The optimization of transportation was systematically analyzed, so was the situation and application of the ant group algorithm. The parameters and the improving method of ant groupalgorithm were studied.(3)A mathematic model with time penalty function for the vehicle-scheduling problem built in this paper and use the improved ant colony algorithm to find the optimal distribution routes. In Solving the distribution routing plans of multi-depots vehicle scheduling problem uses two stages.Firstly,use the nearest principle to divide all customers to different distribution centers and change multi-distribution center problems into a number of single distribution center problems.Then use the improved ant colony algorithm to find the optimal distribution routes in every distribution center. Finally, a satisfied result could be found through continued iterations of the process.