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port-IO: an integrative mobile cloud platform for real-time inter-terminal truck routing optimization

Author

Listed:
  • Leonard Heilig

    (University of Hamburg)

  • Eduardo Lalla-Ruiz

    (University of Hamburg)

  • Stefan Voß

    (University of Hamburg
    Pontificia Universidad Católica de Valparaíso)

Abstract

Besides the transport of containers between transshipment areas, an increasing amount of containers needs to be moved to value-added logistics and auxiliary service areas leading to additional container flows within a seaport. Both real-time information exchange and optimization are necessary to efficiently coordinate actors and container movements being involved in respective inter-terminal transport (ITT). However, there is no decision support system facilitating real-time planning and management of ITT taking advantage of modern information technologies and optimization algorithms. In this paper, we formulate the inter-terminal truck routing problem as a novel optimization problem and propose two greedy heuristics and two hybrid simulated annealing algorithms. The computational experiments, conducted using real locations from the Port of Hamburg (Germany), are evaluated extensively. They indicate that the proposed hybrid simulated annealing algorithms are able to report feasible and improved routes within seconds. The optimization component is embedded into a scalable cloud platform that integrates both real-time data from truck drivers using a mobile app and current traffic data. As such, the proposed mobile cloud platform realizes the vision of a decision support system facilitating real-time communication and context-aware ITT planning for reducing costs and the carbon footprint.

Suggested Citation

  • Leonard Heilig & Eduardo Lalla-Ruiz & Stefan Voß, 2017. "port-IO: an integrative mobile cloud platform for real-time inter-terminal truck routing optimization," Flexible Services and Manufacturing Journal, Springer, vol. 29(3), pages 504-534, December.
    • Handle: RePEc:spr:flsman:v:29:y:2017:i:3:d:10.1007_s10696-017-9280-z
    DOI: 10.1007/s10696-017-9280-z
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    References listed on IDEAS

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    Cited by:

    1. Heilig, Leonard & Lalla-Ruiz, Eduardo & Voß, Stefan, 2017. "Multi-objective inter-terminal truck routing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 178-202.
    2. Leonard Heilig & Eduardo Lalla-Ruiz & Stefan Voß, 2017. "Digital transformation in maritime ports: analysis and a game theoretic framework," Netnomics, Springer, vol. 18(2), pages 227-254, December.
    3. Nurul Haqimin Mohd Salleh & Mahendrran Selvaduray & Jagan Jeevan & Abdul Hafaz Ngah & Suhaiza Zailani, 2021. "Adaptation of Industrial Revolution 4.0 in a Seaport System," Sustainability, MDPI, vol. 13(19), pages 1-13, September.
    4. Torkjazi, Mohammad & Huynh, Nathan & Shiri, Samaneh, 2018. "Truck appointment systems considering impact to drayage truck tours," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 208-228.
    5. Lange, Ann-Kathrin & Nellen, Nicole & Jahn, Carlos, 2022. "Truck appointment systems: How can they be improved and what are their limits?," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Jahn, Carlos & Blecker, Thorsten & Ringle, Christian M. (ed.), Changing Tides: The New Role of Resilience and Sustainability in Logistics and Supply Chain Management – Innovative Approaches for the Shift to a New , volume 33, pages 615-655, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    6. Mar-Ortiz, Julio & Castillo-García, Norberto & Gracia, María D., 2020. "A decision support system for a capacity management problem at a container terminal," International Journal of Production Economics, Elsevier, vol. 222(C).
    7. Qu Hu & Bart Wiegmans & Francesco Corman & Gabriel Lodewijks, 2019. "Integration of inter-terminal transport and hinterland rail transport," Flexible Services and Manufacturing Journal, Springer, vol. 31(3), pages 807-831, September.
    8. Houming Fan & Xiaoxue Ren & Zhenfeng Guo & Yang Li, 2019. "Truck Scheduling Problem Considering Carbon Emissions under Truck Appointment System," Sustainability, MDPI, vol. 11(22), pages 1-23, November.
    9. Marlin W. Ulmer & Leonard Heilig & Stefan Voß, 2017. "On the Value and Challenge of Real-Time Information in Dynamic Dispatching of Service Vehicles," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 59(3), pages 161-171, June.

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