Paper
14 February 2024 Optimization of liner transportation network considering port congestion under public health emergencies
Xiaolong Ren, Jiankun Hu
Author Affiliations +
Proceedings Volume 13018, International Conference on Smart Transportation and City Engineering (STCE 2023); 130185E (2024) https://doi.org/10.1117/12.3024795
Event: International Conference on Smart Transportation and City Engineering (STCE 2023), 2023, Chongqing, China
Abstract
Public health emergencies have caused serious harm to the global trade supply chain, increased the uncertainty of container transportation demand in shipping, and brought great inconvenience to port operations, thus affecting the transportation efficiency of container liner transportation. In this paper, the influence of public health emergencies on liner transportation cost and transportation market is fully considered, and the liner transportation network model with port congestion is constructed, and the PSO algorithm is used to solve the optimization model. On this basis, using the actual data of a liner's port jump under the background of COVID-19 epidemic in 2021 as the research object, the proposed model is verified, and finally the advantages and disadvantages of three heuristic algorithms and CPLEX are compared, and the robustness of the model is analyzed. The results show that PSO algorithm can provide effective calculation results for practical cases, especially in the application of the best combination of different recovery strategies. Convergence experiments and sensitivity analysis experiments show that the proposed optimization model has good accuracy and robustness for liner transportation network optimization under public health emergencies.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Xiaolong Ren and Jiankun Hu "Optimization of liner transportation network considering port congestion under public health emergencies", Proc. SPIE 13018, International Conference on Smart Transportation and City Engineering (STCE 2023), 130185E (14 February 2024); https://doi.org/10.1117/12.3024795
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KEYWORDS
Transportation

Particle swarm optimization

Mathematical optimization

Data modeling

Detection and tracking algorithms

COVID 19

Genetic algorithms

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