Computer Science

Computer Science ›› 2025, Vol. 52 ›› Issue (6A): 240600160-6.doi: 10.11896/jsjkx.240600160

• Artificial Intelligence • Previous Articles     Next Articles

Study on Regional Cold Chain Multimodal Transport Routes Considering Multiple Tasks

SHI Kun1, LI Decang1, MENG Yanbing2, LIU Yatong1   

  1. 1 Mechatronics T&R Institute,Lanzhou Jiaotong University,Lanzhou 730070,China
    2 Graduate School of Lingnan University,Hongkong 999077,China
  • Online:2025-06-16 Published:2025-06-12
  • About author:SHI Kun,born in 1999,postgraduate.His main research interests include multimodal transport and transportation economy.
    LI Decang,born in 1976,Ph.D,senior engineer,Ph.D.His main research in-terests include transportation planning and so on.
  • Supported by:
    Lanzhou Science and Technology Plan Project(2023-1-16).

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Abstract: According to the characteristics of high transportation cost,strong timeliness and high carbon emissions of cold chain logistics transportation,considering the constraints of multi task,carbon emissions,customer satisfaction and transportation arc capacity,a cold chain multimodal transportation path optimization model with the minimum total cost and the highest customer satisfaction is constructed and solved by genetic simulated annealing algorithm.Taking the China regional multimodal transport network from Nanning to Harbin as an example,the paper makes a decision on the intermodal transport scheme,and analyzes the sensitivity of the average temperature of node cities.The results show that the proposed algorithm has faster convergence speed and higher accuracy than the traditional genetic algorithm,and can effectively solve the model.The total satisfaction of the three transportation tasks is 0.53,0.86 and 0.75,respectively.The types of fresh food,customer timeliness requirements and transportation arc capacity will have an impact on the intermodal scheme.The sensitivity analysis results show that: with the increase of urban average temperature,customer satisfaction shows a downward trend.The results of this study can provide some reference for the cold chain multimodal transport route selection under different transportation scenarios.

Key words: Multi-taskpath optimization, Cold chain logistics, Regional multimodal transport, Customer satisfaction, Genetic simulated annealing algorithm

CLC Number: 

  • U169
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