IDEAS home Printed from https://ideas.repec.org/a/inm/ortrsc/v39y2005i2p249-260.html
   My bibliography  Save this article

Minimum Vehicle Fleet Size Under Time-Window Constraints at a Container Terminal

Author

Listed:
  • Iris F. A. Vis

    (School of Economics and Business Administration, Vrije Universiteit Amsterdam, De Boelelaan 1105, Room 3A-31, 1081 HV Amsterdam, The Netherlands)

  • René (M.) B. M. de Koster

    (Rotterdam School of Management/Faculteit Bedrijfskunde, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands)

  • Martin W. P. Savelsbergh

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332)

Abstract

Products can be transported in containers from one port to another. At a container terminal these containers are transshipped from one mode of transportation to another. Cranes remove containers from a ship and put them at a certain time (i.e., release time) into a buffer area with limited capacity. A vehicle lifts a container from the buffer area before the buffer area is full (i.e., in due time) and transports the container from the buffer area to the storage area. At the storage area the container is placed in another buffer area. The advantage of using these buffer areas is the resultant decoupling of the unloading and transportation processes. We study the case in which each container has a time window [release time, due time] in which the transportation should start.The objective is to minimize the vehicle fleet size such that the transportation of each container starts within its time window. No literature has been found studying this relevant problem. We have developed an integer linear programming model to solve the problem of determining vehicle requirements under time-window constraints. We use simulation to validate the estimates of the vehicle fleet size by the analytical model. We test the ability of the model under various conditions. From these numerical experiments we conclude that the results of the analytical model are close to the results of the simulation model. Furthermore, we conclude that the analytical model performs well in the context of a container terminal.

Suggested Citation

  • Iris F. A. Vis & René (M.) B. M. de Koster & Martin W. P. Savelsbergh, 2005. "Minimum Vehicle Fleet Size Under Time-Window Constraints at a Container Terminal," Transportation Science, INFORMS, vol. 39(2), pages 249-260, May.
    • Handle: RePEc:inm:ortrsc:v:39:y:2005:i:2:p:249-260
    DOI: 10.1287/trsc.1030.0063
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/trsc.1030.0063
    Download Restriction: no
    File URL: https://libkey.io/10.1287/trsc.1030.0063?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
    ---><---

    References listed on IDEAS

    as
    1. Mauro Dell'Amico & Matteo Fischetti & Paolo Toth, 1993. "Heuristic Algorithms for the Multiple Depot Vehicle Scheduling Problem," Management Science, INFORMS, vol. 39(1), pages 115-125, January.
    2. I F A Vis & R de Koster & K J Roodbergen & L W P Peeters, 2001. "Determination of the number of automated guided vehicles required at a semi-automated container terminal," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(4), pages 409-417, April.
    3. Vis, Iris F. A. & de Koster, Rene, 2003. "Transshipment of containers at a container terminal: An overview," European Journal of Operational Research, Elsevier, vol. 147(1), pages 1-16, May.
    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. Vis, Iris F.A., 2006. "Survey of research in the design and control of automated guided vehicle systems," European Journal of Operational Research, Elsevier, vol. 170(3), pages 677-709, May.
    2. Tang, Lixin & Zhao, Jiao & Liu, Jiyin, 2014. "Modeling and solution of the joint quay crane and truck scheduling problem," European Journal of Operational Research, Elsevier, vol. 236(3), pages 978-990.
    3. Leonard Heilig & Stefan Voß, 2017. "Inter-terminal transportation: an annotated bibliography and research agenda," Flexible Services and Manufacturing Journal, Springer, vol. 29(1), pages 35-63, March.
    4. Wu, Yue & Luo, Jiabin & Zhang, Dali & Dong, Ming, 2013. "An integrated programming model for storage management and vehicle scheduling at container terminals," Research in Transportation Economics, Elsevier, vol. 42(1), pages 13-27.
    5. 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.
    6. Ulf Speer & Kathrin Fischer, 2017. "Scheduling of Different Automated Yard Crane Systems at Container Terminals," Transportation Science, INFORMS, vol. 51(1), pages 305-324, February.
    7. 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.
    8. Briskorn, Dirk & Drexl, Andreas & Hartmann, Sönke, 2005. "Inventory based dispatching of automated guided vehicles on container terminals," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 596, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    9. Bortfeldt, Andreas & Forster, Florian, 2012. "A tree search procedure for the container pre-marshalling problem," European Journal of Operational Research, Elsevier, vol. 217(3), pages 531-540.
    10. 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.
    11. Daniela Ambrosino & Claudia Caballini, 2019. "New solution approaches for the train load planning problem," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(3), pages 299-325, September.
    12. Kulkarni, Sarang & Krishnamoorthy, Mohan & Ranade, Abhiram & Ernst, Andreas T. & Patil, Rahul, 2018. "A new formulation and a column generation-based heuristic for the multiple depot vehicle scheduling problem," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 457-487.
    13. 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.
    14. Maloni, Michael J. & Jackson, Eric C., 2007. "Stakeholder Contributions to Container Port Capacity: A Survey of Port Authorities," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 46(1).
    15. Yingyi Huang & Yuliya Mamatok & Chun Jin, 2021. "Decision-making instruments for container seaport sustainable development: management platform and system dynamics model," Environment Systems and Decisions, Springer, vol. 41(2), pages 212-226, June.
    16. Timo Gschwind & Stefan Irnich & Simon Emde & Christian Tilk, 2018. "Branch-Cut-and-Price for the Scheduling Deliveries with Time Windows in a Direct Shipping Network," Working Papers 1805, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    17. Feng Li & Jiuh-Biing Sheu & Zi-You Gao, 2015. "Solving the Continuous Berth Allocation and Specific Quay Crane Assignment Problems with Quay Crane Coverage Range," Transportation Science, INFORMS, vol. 49(4), pages 968-989, November.
    18. Goodchild, Anne V. & Daganzo, Carlos F., 2005. "Crane Double Cycling in Container Ports: Affect on Ship Dwell Time," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt9qp7p7jq, Institute of Transportation Studies, UC Berkeley.
    19. Perumal, Shyam S.G. & Lusby, Richard M. & Larsen, Jesper, 2022. "Electric bus planning & scheduling: A review of related problems and methodologies," European Journal of Operational Research, Elsevier, vol. 301(2), pages 395-413.
    20. J Blazewicz & T C E Cheng & M Machowiak & C Oguz, 2011. "Berth and quay crane allocation: a moldable task scheduling model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1189-1197, July.

    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:inm:ortrsc:v:39:y:2005:i:2:p:249-260. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.