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Intermodal Container Routing: Integrating Long-Haul Routing and Local Drayage Decisions

Author

Listed:
  • Hilde Heggen

    (UHasselt, Research Group Logistics, Agoralaan, 3590 Diepenbeek, Belgium
    Maastricht University, Department of Quantitative Economics, P.O. Box 616, 6200 MD Maastricht, The Netherlands)

  • Yves Molenbruch

    (UHasselt, Research Group Logistics, Agoralaan, 3590 Diepenbeek, Belgium
    Research Foundation Flanders (FWO), Egmontstraat 5, 1000 Brussel, Belgium)

  • An Caris

    (UHasselt, Research Group Logistics, Agoralaan, 3590 Diepenbeek, Belgium)

  • Kris Braekers

    (UHasselt, Research Group Logistics, Agoralaan, 3590 Diepenbeek, Belgium)

Abstract

Intermodal logistics service providers decide on the routing of demand through their service network. Long-haul routing decisions determine the selected departure and arrival terminals for containers and imply corresponding drayage tasks. Traditionally, given these long-haul routes and fixed drayage tasks, drayage operations are planned in a second phase by establishing truck routes to transport containers to and from terminals by truck. In this paper, operational decisions on local drayage routing in large-volume freight regions with multiple terminals on the one hand, and intermodal long-haul routing on the other hand are merged into an integrated intermodal routing problem. Different long-haul routing decisions imply different drayage tasks to be performed and thus impact total trucking costs. The approach aims at reducing the number of road kilometres and increases bundling opportunities by maximising the long-haul capacity utilisation. In this way, it contributes to the modal shift towards intermodal transport and a more sustainable transport system. As a weekly planning horizon is used, a maximum daily active time and a minimum overnight’s rest are included for multi-day drayage routing. A large neighbourhood search heuristic is proposed to solve the integrated intermodal routing problem. This integrated planning approach provides decision support for routing customer orders throughout the intermodal network with the aim of minimising total transport costs and maximising capacity utilisation. Experiments show the added value of the integrated approach, which uses more information to make better-informed decisions and increase the capacity utilisation. The largest savings in trucking costs are obtained for clustered instances with demand characteristics closest to real-life cases. Finally, a real-life case study analyses the impact of tactical service network design decisions on the total operational costs.

Suggested Citation

  • Hilde Heggen & Yves Molenbruch & An Caris & Kris Braekers, 2019. "Intermodal Container Routing: Integrating Long-Haul Routing and Local Drayage Decisions," Sustainability, MDPI, vol. 11(6), pages 1-36, March.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:6:p:1634-:d:214979
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    References listed on IDEAS

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    Cited by:

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    2. Snežana Tadić & Milovan Kovač & Mladen Krstić & Violeta Roso & Nikolina Brnjac, 2021. "The Selection of Intermodal Transport System Scenarios in the Function of Southeastern Europe Regional Development," Sustainability, MDPI, vol. 13(10), pages 1-25, May.
    3. Jiahao Zhao & Xiaoning Zhu & Li Wang, 2020. "Study on Scheme of Outbound Railway Container Organization in Rail-Water Intermodal Transportation," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    4. Snežana Tadić & Mladen Krstić & Violeta Roso & Nikolina Brnjac, 2019. "Planning an Intermodal Terminal for the Sustainable Transport Networks," Sustainability, MDPI, vol. 11(15), pages 1-20, July.
    5. 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).
    6. 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).
    7. Xiaodong Li & Haibo Kuang & Yan Hu, 2019. "Carbon Mitigation Strategies of Port Selection and Multimodal Transport Operations—A Case Study of Northeast China," Sustainability, MDPI, vol. 11(18), pages 1-17, September.
    8. Panagiotis Ypsilantis & Rob Zuidwijk, 2019. "Collaborative Fleet Deployment and Routing for Sustainable Transport," Sustainability, MDPI, vol. 11(20), pages 1-26, October.
    9. Molenbruch, Yves & Braekers, Kris & Hirsch, Patrick & Oberscheider, Marco, 2021. "Analyzing the benefits of an integrated mobility system using a matheuristic routing algorithm," European Journal of Operational Research, Elsevier, vol. 290(1), pages 81-98.
    10. Bernard G. Zweers & Sandjai Bhulai & Rob D. Mei, 2021. "Planning hinterland container transportation in congested deep-sea terminals," Flexible Services and Manufacturing Journal, Springer, vol. 33(3), pages 583-622, September.

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