IDEAS home Printed from https://ideas.repec.org/a/pal/marecl/v27y2025i1d10.1057_s41278-024-00290-4.html
   My bibliography  Save this article

Joint scheduling of vessels and vessel service providers for enhancing the efficiency of the port call process

Author

Listed:
  • Shahrzad Nikghadam

    (Port of Rotterdam Authority)

  • Ratnaji Vanga

    (The Delft University of Technology)

  • Jafar Rezaei

    (The Delft University of Technology)

  • Lori Tavasszy

    (The Delft University of Technology)

Abstract

As ports are experiencing heavier traffic, the pressure to improve port call processes is increasing. Port call optimization (PCO) is one of these improvement initiatives, enabling the arrival of vessels to the port just-in-time when the vessel services, like pilotage, towage, and mooring, are all readily available. Otherwise, vessels that sailed at full speed to arrive at the port may have to wait, idling at anchorage, occupying space, burning fuel, and leading to increased congestion. One of the main challenges in the implementation of PCO is determining the time at which availability of these services can be guaranteed. The paper addresses this challenge by presenting a model that jointly schedules vessels and service providers. It extends the current approaches to allow application to larger and busier ports, where repositioning times for pilots and tugboats is highly variable and vessels experience waiting times between services. The problem is formulated as a mixed-integer linear programming one and is modelled in continuous time. We test alternative scheduling strategies using three different objective functions, based on the current ‘first-come-first-serve’ approach, a minimal level of service, and the best capacity utilization. The model is applied on data made available by the Port of Rotterdam, and it provides a full-service schedule for vessels and service providers.

Suggested Citation

  • Shahrzad Nikghadam & Ratnaji Vanga & Jafar Rezaei & Lori Tavasszy, 2025. "Joint scheduling of vessels and vessel service providers for enhancing the efficiency of the port call process," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 27(1), pages 211-236, March.
  • Handle: RePEc:pal:marecl:v:27:y:2025:i:1:d:10.1057_s41278-024-00290-4
    DOI: 10.1057/s41278-024-00290-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41278-024-00290-4
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41278-024-00290-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wei, Xiaoyang & Jia, Shuai & Meng, Qiang & Tan, Kok Choon, 2020. "Tugboat scheduling for container ports," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    2. Ramchandran Jaikumar & Marius M. Solomon, 1987. "The Tug Fleet Size Problem for Barge Line Operations: A Polynomial Algorithm," Transportation Science, INFORMS, vol. 21(4), pages 264-272, November.
    3. Abou Kasm, Omar & Diabat, Ali & Bierlaire, Michel, 2021. "Vessel scheduling with pilotage and tugging considerations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    4. Ulrich Pferschy & Rostislav Staněk, 2017. "Generating subtour elimination constraints for the TSP from pure integer solutions," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(1), pages 231-260, March.
    5. Zhen, Lu & Wang, Kai & Wang, Shuaian & Qu, Xiaobo, 2018. "Tug scheduling for hinterland barge transport: A branch-and-price approach," European Journal of Operational Research, Elsevier, vol. 265(1), pages 119-132.
    6. Wu, Lingxiao & Jia, Shuai & Wang, Shuaian, 2020. "Pilotage planning in seaports," European Journal of Operational Research, Elsevier, vol. 287(1), pages 90-105.
    7. Lee, Chung-Yee & Song, Dong-Ping, 2017. "Ocean container transport in global supply chains: Overview and research opportunities," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 442-474.
    8. Imai, Akio & Nishimura, Etsuko & Papadimitriou, Stratos, 2001. "The dynamic berth allocation problem for a container port," Transportation Research Part B: Methodological, Elsevier, vol. 35(4), pages 401-417, May.
    9. Kang, Liujiang & Meng, Qiang & Tan, Kok Choon, 2020. "Tugboat scheduling under ship arrival and tugging process time uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wei, Xiaoyang & Jia, Shuai & Meng, Qiang & Koh, Jimmy, 2024. "Dynamic tugboat deployment and scheduling with stochastic and time-varying service demands," Transportation Research Part B: Methodological, Elsevier, vol. 188(C).
    2. Hao, Luyao & Jin, Jian Gang & Zhao, Ke, 2023. "Joint scheduling of barges and tugboats for river–sea intermodal transport," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    3. Wei, Xiaoyang & Lau, Hoong Chuin & Xiao, Zhe & Fu, Xiuju & Zhang, Xiaocai & Qin, Zheng, 2025. "Bi-objective dynamic tugboat scheduling with speed optimization under stochastic and time-varying service demands," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 193(C).
    4. Abou Kasm, Omar & Diabat, Ali & Bierlaire, Michel, 2021. "Vessel scheduling with pilotage and tugging considerations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    5. Liu, Baoli & Li, Zhi-Chun & Wang, Yadong, 2022. "A two-stage stochastic programming model for seaport berth and channel planning with uncertainties in ship arrival and handling times," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    6. Zhao, Ke & Jin, Jian Gang & Zhang, Di & Ji, Sheng & Lee, Der-Horng, 2023. "A variable neighborhood search heuristic for real-time barge scheduling in a river-to-sea channel with tidal restrictions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    7. Wei, Xiaoyang & Jia, Shuai & Meng, Qiang & Tan, Kok Choon, 2020. "Tugboat scheduling for container ports," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    8. Guo, Zijian & Cao, Zhen & Wang, Wenyuan & Jiang, Ying & Xu, Xinglu & Feng, Peng, 2021. "An integrated model for vessel traffic and deballasting scheduling in coal export terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    9. Jiachen Li & Xingfeng Duan & Zhennan Xiong & Peng Yao, 2024. "Tugboat Scheduling Method Based on the NRPER-DDPG Algorithm: An Integrated DDPG Algorithm with Prioritized Experience Replay and Noise Reduction," Sustainability, MDPI, vol. 16(8), pages 1-27, April.
    10. Milad Hematian & Jean-François Audy & Mikael Rönnqvist, 2025. "Pilot dispatching problem along a maritime corridor: a case study in the St. Lawrence River," Journal of Shipping and Trade, Springer, vol. 10(1), pages 1-33, December.
    11. Chen, Shukai & Wang, Hua & Meng, Qiang, 2021. "Autonomous truck scheduling for container transshipment between two seaport terminals considering platooning and speed optimization," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 289-315.
    12. Kang, Liujiang & Meng, Qiang & Tan, Kok Choon, 2020. "Tugboat scheduling under ship arrival and tugging process time uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    13. Wang, Shuaian & Zhen, Lu & Zhuge, Dan, 2018. "Dynamic programming algorithms for selection of waste disposal ports in cruise shipping," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 235-248.
    14. Zhen, Lu & Liang, Zhe & Zhuge, Dan & Lee, Loo Hay & Chew, Ek Peng, 2017. "Daily berth planning in a tidal port with channel flow control," Transportation Research Part B: Methodological, Elsevier, vol. 106(C), pages 193-217.
    15. Liu, Baoli & Li, Zhi-Chun & Wang, Yadong, 2023. "A branch-and-price heuristic algorithm for the bunkering operation problem of a liquefied natural gas bunkering station in the inland waterways," Transportation Research Part B: Methodological, Elsevier, vol. 167(C), pages 145-170.
    16. El Mehdi, Er Raqabi & Ilyas, Himmich & Nizar, El Hachemi & Issmaïl, El Hallaoui & François, Soumis, 2023. "Incremental LNS framework for integrated production, inventory, and vessel scheduling: Application to a global supply chain," Omega, Elsevier, vol. 116(C).
    17. Wang, Shuaian & Meng, Qiang, 2012. "Liner ship route schedule design with sea contingency time and port time uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 46(5), pages 615-633.
    18. Liu, Baoli & Li, Zhi-Chun & Sheng, Dian & Wang, Yadong, 2021. "Integrated planning of berth allocation and vessel sequencing in a seaport with one-way navigation channel," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 23-47.
    19. Asghari, Mohammad & Jaber, Mohamad Y. & Mirzapour Al-e-hashem, S.M.J., 2023. "Coordinating vessel recovery actions: Analysis of disruption management in a liner shipping service," European Journal of Operational Research, Elsevier, vol. 307(2), pages 627-644.
    20. Ursavas, Evrim & Zhu, Stuart X., 2016. "Optimal policies for the berth allocation problem under stochastic nature," European Journal of Operational Research, Elsevier, vol. 255(2), pages 380-387.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:marecl:v:27:y:2025:i:1:d:10.1057_s41278-024-00290-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.