Research on Logistics Distribution Route Optimization Based on Artificial Intelligence Technology

DOI: https://doi.org/10.62517/jbm.202609507

Author(s)

Qirou Lu, Guohua Cheng*

Affiliation(s)

School of Digital Economy and Management, Guangdong University of Science and Technology, Dongguan, Guangdong, China *Corresponding Author

Abstract

The vigorous development of the ecommerce industry has driven the rapid iteration of logistics lastmile distribution systems. Current logistics distribution exhibits characteristics of multiple delivery points, fragmentation, and high timeliness requirements. The drawbacks of traditional route planning models dominated by manual experience have become increasingly prominent, including insufficient planning scientificity, redundant routes, poor dynamic adaptability, and high operational costs, making it difficult to meet the demands of smart logistics development. To address these industry pain points, this paper takes artificial intelligence technology as its research vehicle, systematically analyzes the existing deficiencies in traditional logistics distribution route planning, and, by integrating the technical advantages of AI in data processing, global optimization, and dynamic iteration, constructs a route optimization system suitable for small and mediumsized logistics enterprises, proposing targeted intelligent optimization solutions. The research demonstrates that artificial intelligence technology can effectively compensate for the shortcomings of traditional manual scheduling, achieve standardized, refined, and dynamic distribution route planning, significantly improve logistics distribution efficiency, reduce enterprise operational costs, and provide theoretical reference and practical basis for the intelligent transformation of the logistics industry.

Keywords

Artificial Intelligence; Logistics Distribution; Route Optimization; Intelligent Scheduling; Smart Logistics

References

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