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A model for a multi-size inland container transportation problem

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  • Funke, Julia
  • Kopfer, Herbert

Abstract

In the multi-size Inland Container Transportation Problem (mICT) trucks are able to transport up to two 20-foot or one 40-foot container at a time along routes with various pickup and delivery locations. A mixed-integer linear program for the mICT is presented using two alternative objective functions: minimization of the total travel distance and minimization of the total operation time of the trucks. The presented model is tested on instances which vary in size. Computational experiments show that by means of the presented model small problem instances can be solved optimally.

Suggested Citation

  • Funke, Julia & Kopfer, Herbert, 2016. "A model for a multi-size inland container transportation problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 70-85.
    • Handle: RePEc:eee:transe:v:89:y:2016:i:c:p:70-85
    DOI: 10.1016/j.tre.2016.02.010
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    Cited by:

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    3. Song, Yujian & Zhang, Jiantong & Liang, Zhe & Ye, Chunming, 2017. "An exact algorithm for the container drayage problem under a separation mode," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 231-254.
    4. Benantar, A. & Abourraja, M.N. & Boukachour, J. & Boudebous, D. & Duvallet, C., 2020. "On the integration of container availability constraints into daily drayage operations arising in France: Modelling and optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    5. Min Wang & Jiao Ouyang & Lindu Zhao, 2021. "Production planning with transshipment in a global supply chain under different carbon trading mechanisms," Operational Research, Springer, vol. 21(4), pages 2309-2331, December.
    6. Xue, Ning & Bai, Ruibin & Qu, Rong & Aickelin, Uwe, 2021. "A hybrid pricing and cutting approach for the multi-shift full truckload vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 292(2), pages 500-514.
    7. Hajem A. Daham & Xinan Yang & Michaela K. Warnes, 2017. "An efficient mixed integer programming model for pairing containers in inland transportation based on the assignment of orders," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(6), pages 678-694, June.
    8. Bustos-Coral, Daniel & Costa, Alysson M., 2022. "Drayage routing with heterogeneous fleet, compatibility constraints, and truck load configurations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    9. Xinan Yang & Hajem A. Daham, 2020. "A column generation-based decomposition and aggregation approach for combining orders in inland transportation of containers," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(1), pages 261-296, March.
    10. Zhang, Ruiyou & Zhao, Haishu & Moon, Ilkyeong, 2018. "Range-based truck-state transition modeling method for foldable container drayage services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 225-239.
    11. Samaneh Shiri & Nathan Huynh & Daniel Smith & Frank Harder, 2022. "Impact of Second-Tier Container Port Facilities on Drayage Operation," Logistics, MDPI, vol. 6(4), pages 1-21, September.
    12. Van Son Nguyen & Quang Dung Pham & Thanh Trung Huynh, 2024. "Modelling and solving a real-world truck-trailer scheduling problem in container transportation with separate moving objects," OPSEARCH, Springer;Operational Research Society of India, vol. 61(2), pages 628-661, June.
    13. Xuhui Yu & Yin Feng & Cong He & Chang Liu, 2024. "Modeling and Optimization of Container Drayage Problem with Empty Container Constraints across Multiple Inland Depots," Sustainability, MDPI, vol. 16(12), pages 1-32, June.
    14. Escudero-Santana, Alejandro & Muñuzuri, Jesús & Cortés, Pablo & Onieva, Luis, 2021. "The one container drayage problem with soft time windows," Research in Transportation Economics, Elsevier, vol. 90(C).
    15. Dessouky, Maged & Carvajal, Santiago & Yao, Siyuan, 2020. "Congestion Reduction Through Efficient Empty Container Movement Under Stochastic Demand," Institute of Transportation Studies, Working Paper Series qt34c676k1, Institute of Transportation Studies, UC Davis.
    16. Moghaddam, Mahboobeh & Pearce, Robin H. & Mokhtar, Hamid & Prato, Carlo G., 2020. "A generalised model for container drayage operations with heterogeneous fleet, multi-container sizes and two modes of operation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 139(C).
    17. Wenchao Wei & Zining Dong & Jinkui Fan, 2023. "Integrated Location Selection and Scheduling Problems for Inland Container Transportation," Sustainability, MDPI, vol. 15(22), pages 1-16, November.
    18. Chen, Rui & Chen, Shukai & Cui, Haipeng & Meng, Qiang, 2021. "The container drayage problem for heterogeneous trucks with multiple loads: A revisit," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    19. Chen, Rui & Meng, Qiang & Jia, Peng, 2022. "Container port drayage operations and management: Past and future," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    20. Li, Ming & Shao, Saijun & Li, Yang & Zhang, Hua & Zhang, Nianwu & He, Yandong, 2022. "A Physical Internet (PI) based inland container transportation problem with selective non-containerized shipping requests," International Journal of Production Economics, Elsevier, vol. 245(C).
    21. Yujian Song & Yuting Zhang & Wanli Wang & Ming Xue, 2023. "A Branch and Price Algorithm for the Drop-and-Pickup Container Drayage Problem with Empty Container Constraints," Sustainability, MDPI, vol. 15(7), pages 1-28, March.
    22. Arnau, Quim & Barrena, Eva & Panadero, Javier & de la Torre, Rocio & Juan, Angel A., 2022. "A biased-randomized discrete-event heuristic for coordinated multi-vehicle container transport across interconnected networks," European Journal of Operational Research, Elsevier, vol. 302(1), pages 348-362.

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