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Title: Green logistics network optimisation and carbon emission reduction using blockchain technology

Authors: Sitong Liu; Bo Wang

Addresses: School of Management, Guilin University of Aerospace Technology, Guilin, 541004, Guangxi, China; Business School, Guilin University of Electronic Technology, Guilin, 541004, Guangxi, China; Technology Department, Guangxi Yinglun Information Technology Co., Ltd., Nanning, 530007, Guangxi, China ' Business School, Guilin University of Electronic Technology, Guilin, 541004, Guangxi, China

Abstract: This paper explores green logistics network optimisation and carbon emission reduction through blockchain technology, IoT, and big data. A blockchain-based logistics model was developed, incorporating smart contracts for automated carbon management and IoT devices for real-time emission monitoring. Big data analysis enabled logistics path optimisation. Experimental results showed that using ant colony optimisation reduced transportation time by 20%, fuel consumption by 15%, and carbon emissions by 18%. The proposed method enhances logistics efficiency and reduces environmental impact, offering practical solutions and theoretical support for sustainable logistics networks.

Keywords: blockchain technology; green logistics; carbon emissions; path optimisation; smart contracts; IoT; Internet of Things; ACO; ant colony optimisation.

DOI: 10.1504/IJDS.2025.151181

International Journal of Data Science, 2025 Vol.10 No.7, pp.73 - 92

Received: 11 Jan 2025
Accepted: 19 Jun 2025
Published online: 16 Jan 2026 *