Title: Cross-border e-commerce logistics distribution optimisation based on IoT artificial intelligence algorithm

Authors: Haofeng Huang

Addresses: School of Business, Guangdong Polytechnic of Science and Technology, Zhuhai 519090, Guangdong, China

Abstract: In recent years, cross-border e-commerce has developed rapidly, but logistics and distribution still face major obstacles. The emergence of the internet of things (IoT) provides opportunities for it. This paper aims to study the utilisation of IoT in enhancing cross-border e-commerce logistics distribution. This paper determines the ideal logistics distribution path based on the intelligent ant colony algorithm, artificial fish swarm method and a hybrid algorithm combining the two. The experimental results show that the development trend of Taobao's online shopping user scale has increased from 37.65% in 2015 to 59.59% in 2020; the JD online shopping user scale has increased from 30.74% in 2015 to 42.27% in 2020; and Tmall online shopping user scale has increased from 28.53% in 2015 to 34.98% in 2020. The research results show that the optimal path must be selected in logistics distribution to meet the requirements of low cost and high efficiency.

Keywords: logistics distribution optimisation; cross-border e-commerce; artificial intelligence algorithm; internet of things; IoT.

DOI: 10.1504/IJDMB.2024.137745

International Journal of Data Mining and Bioinformatics, 2024 Vol.28 No.2, pp.109 - 126

Received: 16 May 2023
Accepted: 07 Sep 2023
Published online: 04 Apr 2024 *

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