Ant colony algorithm is a path optimization strategy, which uses the information accumulated by the pheromone trajectory to generate a continuous shorter journey, so as to obtain a better solution. The traditional agricultural product logistics route planning has some problems, such as low efficiency and poor safety, and it is difficult to ensure the fast and efficient completion of agricultural product logistics and distribution tasks. Optimization is an ancient problem, reasonable allocation and use of limited resources, the pursuit of the optimal goal is the ideal of human beings. Ant colony algorithm has advantages in solving optimization problems. In order to improve efficiency, the basic algorithm is improved and optimized by rebuilding heuristic function, adopting volatilizing factor strategy and other improvement measures, and a comparative analysis is conducted through simulation experiment. That the improved algorithm in this paper has better operation efficiency, and the logistics transportation path of agricultural products is shorter, and the research content are facilitate to the high-quality development of agricultural products logistics transportation.