Optimal Path Analysis of Fresh Food Logistics and Distribution in 5G Internet of Things Environment

Abstract

Fresh items have become an essential necessity for modern people, and the daily diet structure is growing more and more rich as people’s attention to health increases. One of the characteristics of fresh products is that they are hard to retain at room temperature. As a result, IoT logistics technology assistance is frequently needed in logistics linkages including distribution, transportation, and warehousing. Through the scientific and logical planning of the route of fresh food logistics distribution vehicles, this paper aims to effectively lower the overall economic cost of logistics distribution, guarantee the freshness of the fresh food distribution process, satisfy the various individualized needs of customers for delivery time, and enhance logistics distribution. security. This study suggests an enhanced ant colony algorithm in artificial intelligence that can efficiently determine the shortest path. This algorithm can be used to find the best route for new logistics distribution and lower transportation losses. It is based on 5G Internet of Things technology. The ant colony method prior to the enhancement had the longest optimization time of 25. 06 seconds in the 8 search process, according to the experimental data presented in this study. The enhanced ant colony algorithm had the longest optimization time of 17. 89 seconds. In finding the optimal path, after the improvement, the ant colony algorithm takes less time. In the comparison of transportation costs, the cost of the improved ant colony algorithm is reduced by about 1, 100 yuan, the vehicles required are less than those of the ant colony algorithm before the improvement, and the decay rate is also reduced a lot. It can be seen that the improved ant colony algorithm is more suitable for the analysis of the optimal path of fresh logistics distribution.