An intelligent distribution system for green logistics operations in the blockchain environment

Li, Y., Lin, Y., Lim, M. K. , Xiong, W., Huang, X., Shi, Y. and Su, J. (2024) An intelligent distribution system for green logistics operations in the blockchain environment. International Journal of Logistics Research and Applications, (doi: 10.1080/13675567.2023.2289463) (Early Online Publication)

Abstract

To ensure the safety of fresh food, the cold chain logistics is widely utilised, which can provide a low temperature environment. However, due to the high energy consumption, how to reduce carbon emission of cold chain logistics to develop sustainable distribution has become the research focus. In response, this study proposes an intelligent distribution system for cold chain logistics to achieve green operations. Specifically, the framework of the intelligent system based on blockchain technology is proposed to improve operational efficiency and enhance food traceability. Meanwhile, an electric vehicle routing optimisation model taking into account carbon emission is deployed in the intelligent system to plan the distribution routes. The suggested optimisation model seeks to reduce the total cost, including fixed, spoilage, refrigeration, punishment, queuing, charging and carbon emission costs. Furthermore, an ant colony algorithm is embedded in the intelligent system to help with distribution routes design. Finally, this study combines a real case to discuss the performance of the intelligent system, and the results show that the proposed system can significantly reduce distribution cost and carbon emission. Managers can use the suggested intelligent system to design distribution routes and monitor the distribution process.

• Item Type: Articles
• Additional Information: This research is sponsored by Natural Science Foundation of Chongqing, China (2023NSCQ-BHX0395).
• Keywords: Cold chain logistics, electric vehicle routing, carbon emission, blockchain.
• Status: Early Online Publication
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Lim, Professor Ming
• Authors: Li, Y., Lin, Y., Lim, M. K., Xiong, W., Huang, X., Shi, Y., and Su, J.
• College/School: College of Social Sciences > Adam Smith Business School > Management
• Journal Name: International Journal of Logistics Research and Applications
• Publisher: Taylor and Francis
• ISSN: 1367-5567
• ISSN (Online): 1469-848X
• Published Online: 07 December 2023