Multi-objective Cold Chain Logistics Path Co-Optimization Driven by Minute-by-Minute Road Condition Dynamics

HAO Tongzheng; WANG Xunhong

doi:10.19554/j.cnki.1001-3563.2025.19.020

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Packaging Engineering ›› 2025, Vol. 46 ›› Issue (19) : 184-197. DOI: 10.19554/j.cnki.1001-3563.2025.19.020

Agro-products Preservation and Food Packaging

Multi-objective Cold Chain Logistics Path Co-Optimization Driven by Minute-by-Minute Road Condition Dynamics

HAO Tongzheng¹, WANG Xunhong^1,2*

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Abstract

To address the issues of low delivery efficiency and insufficient multi-objective coordination optimization in cold chain logistics for fresh food e-commerce and pre-cooked meals under urban traffic congestion, the work aims to propose a multi-objective path optimization method that incorporates dynamic traffic conditions, so as to simultaneously improve economic efficiency, customer satisfaction, and product freshness. An optimization model was constructed based on real road networks, integrating traffic congestion indices and road resistance functions. With total cost (including carbon emissions), average customer satisfaction, and average cargo freshness as its multiple objectives, the CMME multi-objective evolutionary algorithm was enhanced. The SLHD was employed for population initialization, optimizing crossover and mutation operators, introducing adaptive strategies, and combining time-dependent A* algorithms to achieve minute-level dynamic path planning. In a real case study conducted at a company in Shenyang, the improved CMME outperformed the original algorithm and other comparison methods in benchmark tests based on IGD and HV metrics. The case study generated 41 Pareto solutions, with the optimal solution achieving a total cost of 1 245.20 yuan, customer satisfaction of 89.44%, and freshness of 94.27%. A carbon tax increase of 0.3 yuan/kg led to a 5.8% rise in total cost. Delaying departure time improved satisfaction, and the spoilage rate of goods significantly affected freshness. The proposed model effectively avoids congestion, and the improved algorithm demonstrates advantages in convergence, distribution, and computational efficiency. It provides decision support for time-sensitive logistics that balance economic, environmental, and service quality objectives, with relevant influencing factors also serving as reference criteria for decision-makers with multiple preferences.

Key words

cold chain logistics / path optimization / congestion index / time-dependent A* algorithm / CMME

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HAO Tongzheng, WANG Xunhong. Multi-objective Cold Chain Logistics Path Co-Optimization Driven by Minute-by-Minute Road Condition Dynamics[J]. Packaging Engineering. 2025, 46(19): 184-197 https://doi.org/10.19554/j.cnki.1001-3563.2025.19.020

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