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Hongkong International Terminals Gains Elastic Capacity Using a Data-Intensive Decision-Support System

Author

Listed:
  • Katta G. Murty

    (Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, Michigan 48109-2117)

  • Yat-wah Wan

    (Institute of Global Operations Strategy and Logistics Management, National Dong Hwa University, Hualien, Taiwan)

  • Jiyin Liu

    (Business School, Loughborough University, Loughborough, Leicestershire LE11 3TU, United Kingdom)

  • Mitchell M. Tseng

    (Department of Industrial Engineering and Engineering Management, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China)

  • Edmond Leung

    (Hongkong International Terminals, Terminal 4, Container Port Road South, Kwai Chung, Hong Kong, China)

  • Kam-Keung Lai

    (Hongkong International Terminals, Terminal 4, Container Port Road South, Kwai Chung, Hong Kong, China)

  • Herman W. C. Chiu

    (Hong Kong Productivity Council, HKPC Building, 78 Tat Chee Avenue, Kowloon, Hong Kong, China)

Abstract

As the flagship of Hutchison Port Holdings (HPH), Hongkong International Terminals (HIT) is the busiest container terminal on the planet. HIT receives over 10,000 trucks and 15 vessels a day, about six million twenty-foot equivalent units (TEUs) a year. HIT makes hundreds of operational decisions a minute. HIT's terminal management system, the productivity plus program (3P), optimizes resources throughout the container yard using operations research/management science (OR/MS) techniques and algorithms. It manages such interrelated decisions as how to route container trucks in the yard, where to store arriving containers, how many quay cranes to use for each vessel, how many trucks to assign to each crane, how many yard cranes to assign to each container storage block, and when to schedule incoming trucks for container pickup. As the number of container terminals in Asia grows, competition has become price driven and service driven. HIT realized its future rests not only with moving boxes but with mastering the associated information. This meant developing a decision-support system (DSS) to provide superior and differentiated services by generating optimal decisions, one that is very robust under uncertain arrival times of trucks and vessels. In its 10 years of operation, the implementation of the DSS through 3P has helped HIT to become the world's most efficient and flexible terminal operator. HIT alone saves US$100 million per year. By optimizing internal truck use at its sister terminals, the HPH group saves an additional US$54 million per year.

Suggested Citation

  • Katta G. Murty & Yat-wah Wan & Jiyin Liu & Mitchell M. Tseng & Edmond Leung & Kam-Keung Lai & Herman W. C. Chiu, 2005. "Hongkong International Terminals Gains Elastic Capacity Using a Data-Intensive Decision-Support System," Interfaces, INFORMS, vol. 35(1), pages 61-75, February.
  • Handle: RePEc:inm:orinte:v:35:y:2005:i:1:p:61-75
    DOI: 10.1287/inte.1040.0120
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    References listed on IDEAS

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    Cited by:

    1. Ku, Dusan & Arthanari, Tiru S., 2016. "Container relocation problem with time windows for container departure," European Journal of Operational Research, Elsevier, vol. 252(3), pages 1031-1039.
    2. Amit Upadhyay, 2021. "Pricing Anomalies and Arbitrage in Container Transport in India," Interfaces, INFORMS, vol. 51(6), pages 422-434, November.
    3. Leonard Heilig & Stefan Voß, 2017. "Information systems in seaports: a categorization and overview," Information Technology and Management, Springer, vol. 18(3), pages 179-201, September.
    4. Nabil Nehme & Bacel Maddah & Isam A. Kaysi, 2021. "An integrated multi-ship crane allocation in Beirut Port container terminal," Operational Research, Springer, vol. 21(3), pages 1743-1761, September.
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    6. Leonard Heilig & Stefan Voß, 0. "Information systems in seaports: a categorization and overview," Information Technology and Management, Springer, vol. 0, pages 1-23.
    7. Jovanovic, Raka & Tuba, Milan & Voß, Stefan, 2019. "An efficient ant colony optimization algorithm for the blocks relocation problem," European Journal of Operational Research, Elsevier, vol. 274(1), pages 78-90.
    8. Li, Dongjun & Dong, Jing-Xin & Song, Dong-Ping & Hicks, Christian & Singh, Surya Prakash, 2020. "Optimal contract design for the exchange of tradable truck permits at multiterminal ports," International Journal of Production Economics, Elsevier, vol. 230(C).
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    10. Amit Upadhyay, 2020. "Improving Intermodal Train Operations in Indian Railways," Interfaces, INFORMS, vol. 50(4), pages 213-224, July.
    11. V. Galle & V. H. Manshadi & S. Borjian Boroujeni & C. Barnhart & P. Jaillet, 2018. "The Stochastic Container Relocation Problem," Transportation Science, INFORMS, vol. 52(5), pages 1035-1058, October.
    12. Zehendner, Elisabeth & Feillet, Dominique & Jaillet, Patrick, 2017. "An algorithm with performance guarantee for the Online Container Relocation Problem," European Journal of Operational Research, Elsevier, vol. 259(1), pages 48-62.
    13. Ahmed M. Abdelmagid & Mohamed Gheith & Amr Eltawil, 2022. "Scheduling External Trucks Appointments in Container Terminals to Minimize Cost and Truck Turnaround Times," Logistics, MDPI, vol. 6(3), pages 1-22, July.
    14. 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.
    15. Sanghyuk Yi & Bernd Scholz-Reiter & Taehoon Kim & Kap Hwan Kim, 2019. "Scheduling appointments for container truck arrivals considering their effects on congestion," Flexible Services and Manufacturing Journal, Springer, vol. 31(3), pages 730-762, September.
    16. Zehendner, Elisabeth & Feillet, Dominique, 2014. "Benefits of a truck appointment system on the service quality of inland transport modes at a multimodal container terminal," European Journal of Operational Research, Elsevier, vol. 235(2), pages 461-469.
    17. Phan, Mai-Ha & Kim, Kap Hwan, 2015. "Negotiating truck arrival times among trucking companies and a container terminal," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 132-144.
    18. Michael F. Gorman & John-Paul Clarke & Amir Hossein Gharehgozli & Michael Hewitt & René de Koster & Debjit Roy, 2014. "State of the Practice: A Review of the Application of OR/MS in Freight Transportation," Interfaces, INFORMS, vol. 44(6), pages 535-554, December.
    19. Chen, Xiaojing & Li, Feng & Jia, Bin & Wu, Jianjun & Gao, Ziyou & Liu, Ronghui, 2021. "Optimizing storage location assignment in an automotive Ro-Ro terminal," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 249-281.
    20. Raka Jovanovic & Milan Tuba & Stefan Voß, 2017. "A multi-heuristic approach for solving the pre-marshalling problem," 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 1-28, March.
    21. Maguire, A. & Ivey, S. & Golias, M.M & Lipinski, M.E, 2010. "Relieving Congestion at Intermodal Marine Container Terminals: Review of Tactical/Operational Strategies," 51st Annual Transportation Research Forum, Arlington, Virginia, March 11-13, 2010 207280, Transportation Research Forum.
    22. Iris F. A. Vis & Hector J. Carlo, 2010. "Sequencing Two Cooperating Automated Stacking Cranes in a Container Terminal," Transportation Science, INFORMS, vol. 44(2), pages 169-182, May.
    23. Raka Jovanovic & Shunji Tanaka & Tatsushi Nishi & Stefan Voß, 2019. "A GRASP approach for solving the Blocks Relocation Problem with Stowage Plan," Flexible Services and Manufacturing Journal, Springer, vol. 31(3), pages 702-729, September.

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