A port-hinterland hub network design method for reefer containers considering time-varying demands and diverse supporting service requirements

Developing an efficient and well-organised reefer container transportation network in the port hinterland is essential for facilitating land-sea perishable product transportation. This paper proposes a port-hinterland hub network design method for reefer containers. Considering the diverse supportin...

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Veröffentlicht in:International journal of production research Jg. 63; H. 20; S. 7525 - 7549
Hauptverfasser: Xu, Xinglu, Wang, Wenyuan, Liu, Keke, Peng, Yun, Cao, Zhen
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Taylor & Francis 18.10.2025
Taylor & Francis LLC
Schlagworte:
cold chain
Container transportation
Containers
Demand
Design techniques
hub location
Network design
Performance evaluation
port hinterland
Registers
Robustness (mathematics)
transportation
Transportation networks
ISSN:0020-7543, 1366-588X
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Zusammenfassung:Developing an efficient and well-organised reefer container transportation network in the port hinterland is essential for facilitating land-sea perishable product transportation. This paper proposes a port-hinterland hub network design method for reefer containers. Considering the diverse supporting service requirements and seasonally time-varying demand of reefer containers, virtual links and nodes were introduced to model a realistic heterogeneous hub deployment issue. This enables hubs to provide various service functions. Additionally, a tailored robustness metric was developed to evaluate network performance under fluctuating demands. The bi-objective network model aims to minimise total costs while maximising network performance. An improved multi-objective particle swarm algorithm is developed to efficiently solve the model. Real case results demonstrate that the proposed method effectively manages network design under time-varying demands. It offers a range of solution schemes with varying levels of time-domain robustness, ensuring stable network performance despite fluctuations in demand. The experiments on the impact of demand seasonality provide operational recommendations for relevant stakeholders. Trial registration Netherlands National Trial Register identifier: NTR-11. . Trial registration Netherlands National Trial Register identifier: NTR-13. . Trial registration Netherlands National Trial Register identifier: NTR-15. . Trial registration Netherlands National Trial Register identifier: NTR-16. . Trial registration Netherlands National Trial Register identifier: NTR-9. .
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ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2025.2501170