Article Details

Abstract

In response to issues such as high transportation costs, insufficient monitoring of last-mile environments, and disconnection between scheduling and execution in cold chain logistics distribution, this paper designs and implements an intelligent three-terminal collaborative platform for cold chain logistics based on the LNS-NSGA2 algorithm. Algorithmically, the freshness decay kinetic model is improved based on the Arrhenius equation. In terms of application, a heterogeneous architecture integrating a Java business hub and a Python computing engine is employed, utilizing WebSocket communication and Redis high-speed caching technology to establish a closed-loop data flow from user order placement and intelligent scheduling to end-to-end temperature control alerts. The logical routes generated by the algorithm are mapped onto actual urban road network trajectories. Meanwhile, the scheduling strategy can be dynamically adjusted based on administrator-defined weights for user satisfaction and transportation costs, thereby reducing transportation capacity waste while ensuring the quality of perishable goods. The platform has considerable engineering value.

Keywords

cold chain logistics; multi-objective optimization; LNS-NSGA2; three-end collaboration; freshness model

References

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Funding

2025 Shaanxi Province College Students Innovation Training Program Project (S202510709083)

About the authors

Zhao Guokun (2006-), male, Han ethnicity, from Xinxiang, Henan Province, undergraduate studies, research direction: intelligent cold chain logistics; Corresponding author: Xue Wensheng (1970-), male, Han ethnicity, from Xi'an, Shaanxi Province, associate professor, master's student, research direction: computer networks.