The design of path optimization in express transportation based on an improved ant colony algorithm

Abstract

With the development of the times, express delivery has become an effective tool for economic competition, where the logistics distribution link is integrated with the Internet, the Internet of Things, big data, and more. The logistics distribution is the direct point of contact with customers and is the most critical part of the entire express delivery process. Among the various costs in express delivery, the cost of distribution is the highest after procurement costs, so the rational arrangement of the distribution plan and the reduction of costs are crucial for maximizing the operational benefits of the entire express company. The Ant Colony algorithm (AC) model studied in this paper is based on the standard AC algorithm, optimizing and improving the AC algorithm and its procedures through elite strategy ant system and maximum-minimum ant system as prerequisites for the Improved Ant Colony algorithm (IAC). Experiments were conducted using the improved algorithm, testing it against specific VRP datasets. The results show that compared with the total path length of the traditional AC, the length of the IAC is optimized by 2.2%; At the same time, the efficiency of the IAC is also greatly improved, which is 64% higher than that of the traditional AC. From this, we can make it clear that the IAC is superior to the traditional AC in all aspects, and it can be applied to express transportation and achieve high efficiency and save time costs.