IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i6p2521-d1089950.html
   My bibliography  Save this article

Modeling and Simulation of Crude Oil Sea–River Transshipment System in China’s Yangtze River Basin

Author

Listed:
  • Yan Yang

    (School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430070, China
    School of Economics and Management, Changzhou Institute of Technology, Changzhou 213032, China)

  • Qiang Zhou

    (School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430070, China)

Abstract

China’s Yangtze River Basin has an increasingly strong demand for crude oil. As a seaborne import port for crude oil, Ningbo-Zhoushan Port is under pressure to undertake the transshipment of crude oil to various oil terminals in the Yangtze River Basin. To alleviate the stress of crude oil transportation in Ningbo-Zhoushan Port, the port operator proposed the crude oil sea–river transshipment scheme in Nantong Port. Therefore, this paper aims to verify the feasibility of this scheme. We used the discrete event system modeling and entity relationship diagram method to construct the hierarchical and concept models of the Yangtze River Basin’s crude oil sea–river transportation system. Furthermore, we developed corresponding simulation modules on the Witness platform and carried out a simulation experiment of the crude oil sea–river transfer scheme. In the experiment, we analyzed the influence of the transshipment ratio on berth utilization, waiting time, and sailing time of other ports by adjusting the parameter of the transshipment ratio. The experimental results show that when the transshipment rate reaches 100%, the utilization rates of loading and unloading berth in Nantong Port are 4% and 13%, respectively, which evidences that Nantong Port has transshipment potential. At the same time, the simulation experiment’s statistical indicators, such as the utilization rate of oil berths, the queuing time of oil tankers, and the sailing time, not only confirm the feasibility of the crude oil sea–river transshipment scheme of Nantong Port but also confirm that the scheme is helpful to improve crude oil transportation efficiency. The simulation results benefit the port operation decision, and the established model and simulation module can be encapsulated and reused.

Suggested Citation

  • Yan Yang & Qiang Zhou, 2023. "Modeling and Simulation of Crude Oil Sea–River Transshipment System in China’s Yangtze River Basin," Energies, MDPI, vol. 16(6), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:6:p:2521-:d:1089950
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/6/2521/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/6/2521/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Schakenbos, Rik & Paix, Lissy La & Nijenstein, Sandra & Geurs, Karst T., 2016. "Valuation of a transfer in a multimodal public transport trip," Transport Policy, Elsevier, vol. 46(C), pages 72-81.
    2. 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.
    3. Nielsen, Otto Anker & Eltved, Morten & Anderson, Marie Karen & Prato, Carlo Giacomo, 2021. "Relevance of detailed transfer attributes in large-scale multimodal route choice models for metropolitan public transport passengers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 76-92.
    4. Rao, Congjun & Zhang, Yue & Wen, Jianghui & Xiao, Xinping & Goh, Mark, 2023. "Energy demand forecasting in China: A support vector regression-compositional data second exponential smoothing model," Energy, Elsevier, vol. 263(PC).
    5. Ur Rehman, Obaid & Ali, Yousaf, 2021. "Optimality study of China’s crude oil imports through China Pakistan economic corridor using fuzzy TOPSIS and Cost-Benefit analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    6. Iris, Çağatay & Pacino, Dario & Ropke, Stefan & Larsen, Allan, 2015. "Integrated Berth Allocation and Quay Crane Assignment Problem: Set partitioning models and computational results," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 81(C), pages 75-97.
    7. Iris, Çağatay & Lam, Jasmine Siu Lee, 2019. "Recoverable robustness in weekly berth and quay crane planning," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 365-389.
    8. Thomas Christensen & Calliope Panoutsou, 2022. "Advanced Biofuel Value Chains through System Dynamics Modelling and Competitive Priorities," Energies, MDPI, vol. 15(2), pages 1-23, January.
    9. Peng, Peng & Yang, Yu & Cheng, Shifen & Lu, Feng & Yuan, Zimu, 2019. "Hub-and-spoke structure: Characterizing the global crude oil transport network with mass vessel trajectories," Energy, Elsevier, vol. 168(C), pages 966-974.
    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, Changchun, 2020. "Iterative heuristic for simultaneous allocations of berths, quay cranes, and yards under practical situations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    2. Xiang, Xi & Liu, Changchun, 2021. "An almost robust optimization model for integrated berth allocation and quay crane assignment problem," Omega, Elsevier, vol. 104(C).
    3. 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.
    4. Cheng Hong & Yufang Guo & Yuhong Wang & Tingting Li, 2023. "The Integrated Scheduling Optimization for Container Handling by Using Driverless Electric Truck in Automated Container Terminal," Sustainability, MDPI, vol. 15(6), pages 1-22, March.
    5. Xufeng Tang & Chang Liu & Xinqi Li & Ying Ji, 2023. "Distributionally Robust Programming of Berth-Allocation-with-Crane-Allocation Problem with Uncertain Quay-Crane-Handling Efficiency," Sustainability, MDPI, vol. 15(18), pages 1-27, September.
    6. Sung Won Cho & Hyun Ji Park & Chulung Lee, 2021. "An integrated method for berth allocation and quay crane assignment to allow for reassignment of vessels to other terminals," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(1), pages 123-153, March.
    7. 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.
    8. Marek Bauer & Piotr Kisielewski, 2021. "The Influence of the Duration of Journey Stages on Transport Mode Choice: A Case Study in the City of Tarnow," Sustainability, MDPI, vol. 13(11), pages 1-15, May.
    9. Yang, Weixin & Pan, Lingying & Ding, Qinyi, 2023. "Dynamic analysis of natural gas substitution for crude oil: Scenario simulation and quantitative evaluation," Energy, Elsevier, vol. 282(C).
    10. Meixian Jiang & Jiajia Feng & Jian Zhou & Lin Zhou & Fangzheng Ma & Guanghua Wu & Yuqiu Zhang, 2023. "Multi-Terminal Berth and Quay Crane Joint Scheduling in Container Ports Considering Carbon Cost," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    11. Chargui, Kaoutar & Zouadi, Tarik & El Fallahi, Abdellah & Reghioui, Mohamed & Aouam, Tarik, 2021. "Berth and quay crane allocation and scheduling with worker performance variability and yard truck deployment in container terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
    12. Biao Yin & Fabien Leurent, 2022. "Estimation of Transfer Time from Multimodal Transit Services in the Paris Region," Post-Print hal-03841390, HAL.
    13. 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.
    14. Sara Ezquerro & José Luis Moura & Borja Alonso, 2020. "Illegal Use of Loading Bays and Its Impact on the Use of Public Space," Sustainability, MDPI, vol. 12(15), pages 1-16, July.
    15. Xiang Li & Qipeng Yan & Yafeng Ma & Chen Luo, 2023. "Spatially Varying Impacts of Built Environment on Transfer Ridership of Metro and Bus Systems," Sustainability, MDPI, vol. 15(10), pages 1-24, May.
    16. Rodrigues, Filipe & Agra, Agostinho, 2022. "Berth allocation and quay crane assignment/scheduling problem under uncertainty: A survey," European Journal of Operational Research, Elsevier, vol. 303(2), pages 501-524.
    17. Dafnomilis, I. & Duinkerken, M.B. & Junginger, M. & Lodewijks, G. & Schott, D.L., 2018. "Optimal equipment deployment for biomass terminal operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 147-163.
    18. Lijun Meng & Qiang Qiang & Zuqing Huang & Baoyou Zhang & Yuxiang Yang, 2020. "Optimal Pricing Strategy and Government Consumption Subsidy Policy in Closed-Loop Supply Chain with Third-Party Remanufacturer," Sustainability, MDPI, vol. 12(6), pages 1-29, March.
    19. 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.
    20. Agra, Agostinho & Oliveira, Maryse, 2018. "MIP approaches for the integrated berth allocation and quay crane assignment and scheduling problem," European Journal of Operational Research, Elsevier, vol. 264(1), pages 138-148.

    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:jeners:v:16:y:2023:i:6:p:2521-:d:1089950. 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.