Design and Application of Improved Ant Colony Algorithm in E-Commerce System

Abstract

Since the 21st century, artificial intelligence and e-commerce have taken the lead. The two are close to life. Data show that, in the digital economy era, the two have developed rapidly and are widely used; however, they also have some problems. E-commerce logistics system has always been the first problem mentioned by relevant personnel and users. The continuous increase in transaction volume is worth celebrating, but the logistics efficiency continues to be flat or even declining, which has become a serious problem. This shows that, for the e-commerce platform, the investment in science and technology is not comprehensive and in depth, and the artificial intelligence technology has not been deeply applied for the logistics industry. Understanding needs, finding problems, and solving them in time are the way to develop this industry. Pareto is chosen by most logistics systems, but in fact, its efficiency is not as high as imagined. In view of this, this paper proposes an innovative algorithm, based on ant colony algorithm, with optimization mechanism to strengthen the shortcomings, thus improving the premature problem of ant colony algorithm, and at the same time, a series of performances such as convergence speed, accuracy, and stability have been strengthened because of this improvement. Experiments show that the optimization ability of this algorithm is better than the other two.