Location Optimization of Fresh Agricultural Products Distribution Center Based on Particle Swarm Optimization Neural Network

High transportation cost is a major feature of fresh agricultural products distribution, how to effectively optimize the path, and then reduce transportation cost is the key method to promote the development of fresh logistics. In contrast to the good development prospects of the cold chain logistics market of fresh agricultural products, the development of India's cold chain logistics industry has entered a bottleneck period. According to the characteristics of fresh agricultural products with short preservation period, the mathematical model of location problem of multiple distribution centers with time constraint was established in order to save various operating costs and minimize investment costs. Traffic flow prediction is the basis of traffic control and guidance. The traditional traffic flow prediction technology has been unable to meet the actual demand, and some prediction methods with higher accuracy, especially intelligent calculation methods, keep emerging. Through the optimization of the whole system, to achieve the standardization of the whole system, standardized development, to improve the circulation quality and efficiency of fresh agricultural products, promote the rapid and healthy development of Modern agriculture in India, is of great significance. The key of cooperative distribution is to distribute the profit reasonably among distribution centers. Therefore, the topic of this paper has important practical significance in solving practical problems.