IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v198y2020ics0951832018314789.html
   My bibliography  Save this article

Liner-dedicated manageability estimation for port operational reliability

Author

Listed:
  • Park, Jaehun
  • Lee, Byung Kwon

Abstract

A container port consists of various sub-systems such as berth, block, gate, etc., which consists of different types of machines where containers are handled. Much research has been conducted on improving operational performance of a container port over the past decades by enhancing the handling efficiency at each sub-system, eliminating unproductive moves, and synchronizing the handshake activities between them. The high operational performance is achieved by efficiently scheduling handling activities of containers for each ship based on standardized operational processes, unless unexpected events disrupt container workflows in the operational processes. Therefore, it is imperative to effectively control the operational processes by looking into the manageability of container workflows. This study employs an event-based learning approach to analyze the operational discrepancy of container workflows in operational processes and estimate operational manageability in view of the proposed management components (i.e., logistics, machine, and time) from the analytical outcomes. The comparative experiments were conducted on a real-world dataset to estimate the operational manageability of a container port for ships of various shipping liners.

Suggested Citation

  • Park, Jaehun & Lee, Byung Kwon, 2020. "Liner-dedicated manageability estimation for port operational reliability," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    • Handle: RePEc:eee:reensy:v:198:y:2020:i:c:s0951832018314789
    DOI: 10.1016/j.ress.2020.106897
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832018314789
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2020.106897?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. Carlo, Héctor J. & Vis, Iris F.A. & Roodbergen, Kees Jan, 2014. "Transport operations in container terminals: Literature overview, trends, research directions and classification scheme," European Journal of Operational Research, Elsevier, vol. 236(1), pages 1-13.
    2. Zhang, Yi & Lam, Jasmine Siu Lee, 2016. "Estimating economic losses of industry clusters due to port disruptions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 17-33.
    3. Branislav Dragović & Ernestos Tzannatos & Nam Kuy Park, 2017. "Simulation modelling in ports and container terminals: literature overview and analysis by research field, application area and tool," Flexible Services and Manufacturing Journal, Springer, vol. 29(1), pages 4-34, March.
    4. Wil M. P. Aalst, 2015. "Extracting Event Data from Databases to Unleash Process Mining," Management for Professionals, in: Jan vom Brocke & Theresa Schmiedel (ed.), BPM - Driving Innovation in a Digital World, edition 127, pages 105-128, Springer.
    5. Liu, Honglu & Tian, Zhihong & Huang, Anqiang & Yang, Zaili, 2018. "Analysis of vulnerabilities in maritime supply chains," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 475-484.
    6. Yuan Yuan & Shiyu Zhou & Crispian Sievenpiper & Kamal Mannar & Yibin Zheng, 2011. "Event log modeling and analysis for system failure prediction," IISE Transactions, Taylor & Francis Journals, vol. 43(9), pages 647-660.
    7. Almutairi, Ayedh & Collier, Zachary A. & Hendrickson, Daniel & Palma-Oliveira, José M. & Polmateer, Thomas L. & Lambert, James H., 2019. "Stakeholder mapping and disruption scenarios with application to resilience of a container port," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 219-232.
    8. Reder, Maik & Yürüşen, Nurseda Y. & Melero, Julio J., 2018. "Data-driven learning framework for associating weather conditions and wind turbine failures," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 554-569.
    9. Aziz, Abdul & Ahmed, Salim & Khan, Faisal & Stack, Chris & Lind, Annes, 2019. "Operational risk assessment model for marine vessels," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 348-361.
    10. Gillen, David & Hasheminia, Hamed, 2016. "Measuring reliability of transportation networks using snapshots of movements in the network – An analytical and empirical study," Transportation Research Part B: Methodological, Elsevier, vol. 93(PB), pages 808-824.
    11. Ha, Min-Ho & Yang, Zaili, 2017. "Comparative analysis of port performance indicators: Independency and interdependency," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 264-278.
    12. Lehnfeld, Jana & Knust, Sigrid, 2014. "Loading, unloading and premarshalling of stacks in storage areas: Survey and classification," European Journal of Operational Research, Elsevier, vol. 239(2), pages 297-312.
    13. Carlo, Héctor J. & Vis, Iris F.A. & Roodbergen, Kees Jan, 2014. "Storage yard operations in container terminals: Literature overview, trends, and research directions," European Journal of Operational Research, Elsevier, vol. 235(2), pages 412-430.
    14. Kap Hwan Kim & Hoon Lee, 2015. "Container Terminal Operation: Current Trends and Future Challenges," International Series in Operations Research & Management Science, in: Chung-Yee Lee & Qiang Meng (ed.), Handbook of Ocean Container Transport Logistics, edition 127, chapter 2, pages 43-73, Springer.
    15. Gehl, Pierre & Cavalieri, Francesco & Franchin, Paolo, 2018. "Approximate Bayesian network formulation for the rapid loss assessment of real-world infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 80-93.
    16. Zhou, Ying & Li, Chenshuang & Zhou, Cheng & Luo, Hanbin, 2018. "Using Bayesian network for safety risk analysis of diaphragm wall deflection based on field data," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 152-167.
    17. Barabadi, A. & Ayele, Y.Z., 2018. "Post-disaster infrastructure recovery: Prediction of recovery rate using historical data," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 209-223.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dui, Hongyan & Zheng, Xiaoqian & Wu, Shaomin, 2021. "Resilience analysis of maritime transportation systems based on importance measures," Reliability Engineering and System Safety, Elsevier, vol. 209(C).

    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. Amir Gharehgozli & Nima Zaerpour & Rene Koster, 2020. "Container terminal layout design: transition and future," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 22(4), pages 610-639, December.
    2. Wang, Ning & Jin, Bo & Zhang, Zizhen & Lim, Andrew, 2017. "A feasibility-based heuristic for the container pre-marshalling problem," European Journal of Operational Research, Elsevier, vol. 256(1), pages 90-101.
    3. Domenico Gattuso & Domenica Savia Pellicanò, 2023. "HUs Fleet Management in an Automated Container Port: Assessment by a Simulation Approach," Sustainability, MDPI, vol. 15(14), pages 1-19, July.
    4. de Melo da Silva, Marcos & Toulouse, Sophie & Wolfler Calvo, Roberto, 2018. "A new effective unified model for solving the Pre-marshalling and Block Relocation Problems," European Journal of Operational Research, Elsevier, vol. 271(1), pages 40-56.
    5. Geoffrey C. Preston & Phillip Horne & Maria Paola Scaparra & Jesse R. O’Hanley, 2020. "Masterplanning at the Port of Dover: The Use of Discrete-Event Simulation in Managing Road Traffic," Sustainability, MDPI, vol. 12(3), pages 1-19, February.
    6. Kastner, Marvin & Kämmerling, Nicolas & Jahn, Carlos & Clausen, Uwe, 2020. "Equipment selection and layout planning - Literature overview and research directions," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability. Proceedings of the Hamburg International Conferen, volume 30, pages 485-519, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    7. Lennart Zey & Dirk Briskorn & Nils Boysen, 2022. "Twin-crane scheduling during seaside workload peaks with a dedicated handshake area," Journal of Scheduling, Springer, vol. 25(1), pages 3-34, February.
    8. Ruiyou Zhang & Shixin Liu & Herbert Kopfer, 2016. "Tree search procedures for the blocks relocation problem with batch moves," Flexible Services and Manufacturing Journal, Springer, vol. 28(3), pages 397-424, September.
    9. Gharehgozli, Amir & Zaerpour, Nima, 2018. "Stacking outbound barge containers in an automated deep-sea terminal," European Journal of Operational Research, Elsevier, vol. 267(3), pages 977-995.
    10. Kevin Tierney & Dario Pacino & Stefan Voß, 2017. "Solving the pre-marshalling problem to optimality with A* and IDA," Flexible Services and Manufacturing Journal, Springer, vol. 29(2), pages 223-259, June.
    11. Facchini, F. & Digiesi, S. & Mossa, G., 2020. "Optimal dry port configuration for container terminals: A non-linear model for sustainable decision making," International Journal of Production Economics, Elsevier, vol. 219(C), pages 164-178.
    12. Zweers, Bernard G. & Bhulai, Sandjai & van der Mei, Rob D., 2020. "Optimizing pre-processing and relocation moves in the Stochastic Container Relocation Problem," European Journal of Operational Research, Elsevier, vol. 283(3), pages 954-971.
    13. Damla Kizilay & Deniz Türsel Eliiyi, 2021. "A comprehensive review of quay crane scheduling, yard operations and integrations thereof in container terminals," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 1-42, March.
    14. Gharehgozli, Amir & Yu, Yugang & de Koster, René & Du, Shaofu, 2019. "Sequencing storage and retrieval requests in a container block with multiple open locations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 261-284.
    15. Feng, Yuanjun & Song, Dong-Ping & Li, Dong & Zeng, Qingcheng, 2020. "The stochastic container relocation problem with flexible service policies," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 116-163.
    16. Ting, Ching-Jung & Wu, Kun-Chih, 2017. "Optimizing container relocation operations at container yards with beam search," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 17-31.
    17. Wiercx, Max & van Kalmthout, Martijn & Wiegmans, Bart, 2019. "Inland waterway terminal yard configuration contributing to sustainability: Modeling yard operations," Research in Transportation Economics, Elsevier, vol. 73(C), pages 4-16.
    18. Gharehgozli, Amir Hossein & Vernooij, Floris Gerardus & Zaerpour, Nima, 2017. "A simulation study of the performance of twin automated stacking cranes at a seaport container terminal," European Journal of Operational Research, Elsevier, vol. 261(1), pages 108-128.
    19. Zhou, Chenhao & Lee, Byung Kwon & Li, Haobin, 2020. "Integrated optimization on yard crane scheduling and vehicle positioning at container yards," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    20. Bierwirth, Christian & Meisel, Frank, 2015. "A follow-up survey of berth allocation and quay crane scheduling problems in container terminals," European Journal of Operational Research, Elsevier, vol. 244(3), pages 675-689.

    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:eee:reensy:v:198:y:2020:i:c:s0951832018314789. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.