Vehicle routing optimization based on traditional and improved ant colony algorithm

With the rapid development of cold chain logistics industry, reducing the cold chain logistics transportation cost and saving transportation time have become the research focus in the logistics industry. In this case, the traditional ant colony algorithm path planning can no longer meet the current vehicle scheduling system. Based on this situation, the traditional ant colony algorithm is optimized and improved to ensure that the cold chain logistics vehicle path is in the optimal state. In this paper, the pheromone concentration released by the optimal path in the crawling process of ants is used to modify the calculation formula. Meanwhile, the transfer probability of ants will change when they are affected by the hot search area. By changing the path of the traditional ant colony algorithm, the traveling path of the cold chain logistics vehicle is optimized and the transportation cost is reduced.