IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i1p403-d1312111.html
   My bibliography  Save this article

A Novel Virtual Arrival Optimization Method for Traffic Organization Scenarios

Author

Listed:
  • Tianhao Shao

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
    Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
    National Traffic Management Engineering & Technology Research Center Ningbo University Sub-Center, Ningbo 315832, China)

  • Weijie Du

    (Ningbo Pilot Station, Ningbo 315040, China)

  • Yun Ye

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
    Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
    National Traffic Management Engineering & Technology Research Center Ningbo University Sub-Center, Ningbo 315832, China)

  • Haoqing Li

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
    Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
    National Traffic Management Engineering & Technology Research Center Ningbo University Sub-Center, Ningbo 315832, China)

  • Jingxin Dong

    (Business School, Newcastle University, Newcastle upon Tyne NE1 ASE, UK)

  • Guiyun Liu

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
    Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
    National Traffic Management Engineering & Technology Research Center Ningbo University Sub-Center, Ningbo 315832, China)

  • Pengjun Zheng

    (Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211, China
    Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 211189, China
    National Traffic Management Engineering & Technology Research Center Ningbo University Sub-Center, Ningbo 315832, China)

Abstract

The International Maritime Organization (IMO) has been progressively implementing stricter regulations on ship carbon emissions, leading to many vessels adopting the virtual arrival (VA) method to reduce their carbon footprint. However, the effectiveness of the traditional VA method often varies in busy ports with complex traffic organization scenarios. To address this, our study presents a novel, comprehensive model that integrates vessel scheduling with the VA approach. This model is designed to achieve a dual objective: reducing carbon emissions through virtual arrival while simultaneously minimizing vessel waiting times. In addition to these goals, it incorporates essential aspects of safety, efficiency, and fairness in port management, utilizing the NSGA-2 algorithm to find optimal solutions. This model has been tested and validated through a case study at Ningbo-Zhoushan port, employing its dataset. The results demonstrate that our innovative model and algorithm significantly outperform traditional scheduling methods, such as First-Come-First-Serve (FCFS) and Virtual-Arrival Last-Serve (VALS), particularly in terms of operational efficiency and reduction in vessel carbon emissions.

Suggested Citation

  • Tianhao Shao & Weijie Du & Yun Ye & Haoqing Li & Jingxin Dong & Guiyun Liu & Pengjun Zheng, 2024. "A Novel Virtual Arrival Optimization Method for Traffic Organization Scenarios," Sustainability, MDPI, vol. 16(1), pages 1-17, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:1:p:403-:d:1312111
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/1/403/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/1/403/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bin Zhang & Zhongyi Zheng & Deqiang Wang, 2020. "A model and algorithm for vessel scheduling through a two-way tidal channel," Maritime Policy & Management, Taylor & Francis Journals, vol. 47(2), pages 188-202, February.
    2. Unsal, Ozgur & Oguz, Ceyda, 2019. "An exact algorithm for integrated planning of operations in dry bulk terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 103-121.
    3. 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.
    4. Yuquan Du & Qiushuang Chen & Jasmine Siu Lee Lam & Ya Xu & Jin Xin Cao, 2015. "Modeling the Impacts of Tides and the Virtual Arrival Policy in Berth Allocation," Transportation Science, INFORMS, vol. 49(4), pages 939-956, November.
    5. J Fernando Alvarez & Tore Longva & Erna S Engebrethsen, 2010. "A methodology to assess vessel berthing and speed optimization policies," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 12(4), pages 327-346, December.
    6. Patrizia Serra & Gianfranco Fancello, 2020. "Towards the IMO’s GHG Goals: A Critical Overview of the Perspectives and Challenges of the Main Options for Decarbonizing International Shipping," Sustainability, MDPI, vol. 12(8), pages 1-32, April.
    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. 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).
    2. 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).
    3. 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.
    4. 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.
    5. Zhen, Lu & Zhuge, Dan & Wang, Shuaian & Wang, Kai, 2022. "Integrated berth and yard space allocation under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 1-27.
    6. Raeesi, Ramin & Sahebjamnia, Navid & Mansouri, S. Afshin, 2023. "The synergistic effect of operational research and big data analytics in greening container terminal operations: A review and future directions," European Journal of Operational Research, Elsevier, vol. 310(3), pages 943-973.
    7. Jia, Shuai & Li, Chung-Lun & Xu, Zhou, 2020. "A simulation optimization method for deep-sea vessel berth planning and feeder arrival scheduling at a container port," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 174-196.
    8. Yu, Jingjing & Tang, Guolei & Song, Xiangqun, 2022. "Collaboration of vessel speed optimization with berth allocation and quay crane assignment considering vessel service differentiation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    9. 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).
    10. Guo, Liming & Zheng, Jianfeng & Du, Haoming & Du, Jian & Zhu, Zhihong, 2022. "The berth assignment and allocation problem considering cooperative liner carriers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    11. Hamza Bouzekri & Gülgün Alpan & Vincent Giard, 2022. "Integrated Laycan and Berth Allocation Problem with ship stability and conveyor routing constraints in bulk ports," Working Papers hal-03431793, HAL.
    12. 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.
    13. Kwang-Il Kim & Keon Myung Lee, 2018. "Dynamic Programming-Based Vessel Speed Adjustment for Energy Saving and Emission Reduction," Energies, MDPI, vol. 11(5), pages 1-15, May.
    14. Peter Andersson & Pernilla Ivehammar, 2017. "Dynamic route planning in the Baltic Sea Region – A cost-benefit analysis based on AIS data," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(4), pages 631-649, December.
    15. Xing, Hui & Spence, Stephen & Chen, Hua, 2020. "A comprehensive review on countermeasures for CO2 emissions from ships," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    16. Orestis Schinas & Niklas Bergmann, 2021. "The Short-Term Cost of Greening the Global Fleet," Sustainability, MDPI, vol. 13(16), pages 1-32, August.
    17. Wang, Tingsong & Wang, Xinchang & Meng, Qiang, 2018. "Joint berth allocation and quay crane assignment under different carbon taxation policies," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 18-36.
    18. Suneet Singh & Ashish Dwivedi & Saurabh Pratap, 2023. "Sustainable Maritime Freight Transportation: Current Status and Future Directions," Sustainability, MDPI, vol. 15(8), pages 1-23, April.
    19. Xiwen Bai & Jesús Fernández-Villaverde & Yiliang Li & Francesco Zanetti, 2024. "The Causal Effects of Global Supply Chain Disruptions on Macroeconomic Outcomes: Evidence and Theory," Economics Series Working Papers 1033, University of Oxford, Department of Economics.
    20. Zhen, Lu & Wang, Shuaian & Zhuge, Dan, 2017. "Dynamic programming for optimal ship refueling decision," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 100(C), pages 63-74.

    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:gam:jsusta:v:16:y:2024:i:1:p:403-:d:1312111. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.