Journal of Engineering, Project, and Production Management, 2026, 16(6), 2025-263
Cross-Border Fresh Product Transportation Optimization via Multi-Objective Models and Hybrid Algorithms
1 Instructor,
Digital Business College, Heilongjiang Polytechnic, Harbin, 150001,
China,
2 Instructor, Digital Business
College, Heilongjiang Polytechnic, Harbin, 150001, China,
E-mail: zhangguangwen2025@163.com (corresponding author).
Production Management
Received November 10, 2025; revised January 26, 2026; accepted June 21, 2026
Available online July 2, 2026
Abstract: The transportation of cross-border fresh products is characterized by high time sensitivity and intense vulnerability to spoilage. However, most existing studies overlook the randomness of customs clearance, which limits the practical application of routing plans. Therefore, this study proposes a transportation route optimization model for cross-border e-commerce of fresh products based on multi-objective optimization and hybrid algorithms. It fully leverages the hunting mechanism of the Harris Hawks Optimization (HHO) algorithm to enhance local exploitation, and improves the inertia weight of the Particle Swarm Optimization (PSO) algorithm by predicting traffic congestion and customs delays using Weighted Random Forest (WRF). Experimental results show that the receiver operating characteristic curve of the proposed model is closest to the upper-left corner, with an area under the curve reaching 0.89, indicating better classification performance and predictive accuracy. The model also achieves F1 scores above 80%, with an annual average satisfaction rate of 92.2% for timelines. The average annual satisfaction rate for quality is 94.3%, 17.9% higher than that of the traditional weighted random forest algorithm. These results demonstrate that the proposed model achieves significant optimization performance in cross-border e-commerce fresh-product transportation scenarios. It effectively improves logistics efficiency and provides a multi-objective solution balancing cost and quality for the industry.
Keywords: Multi-objective model; hybrid algorithm; fresh products; route optimization; harris hawks optimization (HHO).
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Citation: Chen, Z., and Zhang, G. (2026). Cross-Border Fresh Product Transportation Optimization via Multi-Objective Models and Hybrid Algorithms. Journal of Engineering, Project, and Production Management, 16(6), 2025-263.
