IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v141y2013i1p179-188.html
   My bibliography  Save this article

Managing truck arrivals with time windows to alleviate gate congestion at container terminals

Author

Listed:
  • Chen, Gang
  • Govindan, Kannan
  • Yang, Zhongzhen

Abstract

Long truck queues at gates often limit the efficiency of a container terminal and generate serious air pollution. To reduce the gate congestion, this paper proposes a method called ‘vessel dependent time windows (VDTWs)' to control truck arrivals, which involves partitioning truck entries into groups and assigning different time windows to the groups. The proposed VDTWs method includes three steps: (1) predicting truck arrivals based on the time window assignment, (2) estimating the queue length of trucks, and (3) optimizing the arrangement of time windows to minimize the total cost in the system. A conventional Genetic Algorithm (GA), a multi-society GA, and a hybrid algorithm using GA and Simulated Annealing are used to solve the optimization problem. A case study based on a real container terminal in China is performed, which shows the VDTWs method can flatten the truck arrivals and reduce the gate congestion significantly.

Suggested Citation

  • Chen, Gang & Govindan, Kannan & Yang, Zhongzhen, 2013. "Managing truck arrivals with time windows to alleviate gate congestion at container terminals," International Journal of Production Economics, Elsevier, vol. 141(1), pages 179-188.
    • Handle: RePEc:eee:proeco:v:141:y:2013:i:1:p:179-188
    DOI: 10.1016/j.ijpe.2012.03.033
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527312001417
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijpe.2012.03.033?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. Namboothiri, Rajeev & Erera, Alan L., 2008. "Planning local container drayage operations given a port access appointment system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(2), pages 185-202, March.
    2. Linda Green & Peter Kolesar, 1991. "The Pointwise Stationary Approximation for Queues with Nonstationary Arrivals," Management Science, INFORMS, vol. 37(1), pages 84-97, January.
    3. Gang Chen & Zhongzhen Yang, 2010. "Optimizing time windows for managing export container arrivals at Chinese container terminals," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 12(1), pages 111-126, March.
    4. Changqian Guan & Rongfang (Rachel) Liu, 2009. "Container terminal gate appointment system optimization," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 11(4), pages 378-398, December.
    5. Taniguchi, Eiichi & Noritake, Michihiko & Yamada, Tadashi & Izumitani, Toru, 1999. "Optimal size and location planning of public logistics terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 35(3), pages 207-222, September.
    6. Kim, Seongmoon, 2009. "The toll plaza optimization problem: Design, operations, and strategies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(1), pages 125-137, January.
    7. Zhao, Wenjuan & Goodchild, Anne V., 2010. "The impact of truck arrival information on container terminal rehandling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(3), pages 327-343, May.
    8. Stolletz, Raik, 2008. "Approximation of the non-stationary M(t)/M(t)/c(t)-queue using stationary queueing models: The stationary backlog-carryover approach," European Journal of Operational Research, Elsevier, vol. 190(2), pages 478-493, October.
    9. Zegordi, S.H. & Beheshti Nia, M.A., 2009. "A multi-population genetic algorithm for transportation scheduling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(6), pages 946-959, November.
    10. Chen, Xiaoming & Zhou, Xuesong & List, George F., 2011. "Using time-varying tolls to optimize truck arrivals at ports," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 965-982.
    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. Chen, Gang & Govindan, Kannan & Yang, Zhong-Zhen & Choi, Tsan-Ming & Jiang, Liping, 2013. "Terminal appointment system design by non-stationary M(t)/Ek/c(t) queueing model and genetic algorithm," International Journal of Production Economics, Elsevier, vol. 146(2), pages 694-703.
    2. Gharehgozli, A.H. & Roy, D. & de Koster, M.B.M., 2014. "Sea Container Terminals," ERIM Report Series Research in Management ERS-2014-009-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Torkjazi, Mohammad & Huynh, Nathan & Shiri, Samaneh, 2018. "Truck appointment systems considering impact to drayage truck tours," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 208-228.
    4. 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.
    5. Lange, Ann-Kathrin & Nellen, Nicole & Jahn, Carlos, 2022. "Truck appointment systems: How can they be improved and what are their limits?," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Jahn, Carlos & Blecker, Thorsten & Ringle, Christian M. (ed.), Changing Tides: The New Role of Resilience and Sustainability in Logistics and Supply Chain Management – Innovative Approaches for the Shift to a New , volume 33, pages 615-655, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    6. Mohammad Torkjazi & Nathan Huynh & Ali Asadabadi, 2022. "Modeling the Truck Appointment System as a Multi-Player Game," Logistics, MDPI, vol. 6(3), pages 1-25, July.
    7. Chen, Gang & Govindan, Kannan & Golias, Mihalis M., 2013. "Reducing truck emissions at container terminals in a low carbon economy: Proposal of a queueing-based bi-objective model for optimizing truck arrival pattern," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 55(C), pages 3-22.
    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).
    9. Xiaoju Zhang & Qingcheng Zeng & Zhongzhen Yang, 2019. "Optimization of truck appointments in container terminals," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(1), pages 125-145, March.
    10. Kap Hwan Kim & Sanghyuk Yi, 2021. "Utilizing information sources to reduce relocation of inbound containers," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(4), pages 726-749, December.
    11. María D. Gracia & Rosa G. González-Ramírez & Julio Mar-Ortiz, 2017. "The impact of lanes segmentation and booking levels on a container terminal gate congestion," Flexible Services and Manufacturing Journal, Springer, vol. 29(3), pages 403-432, December.
    12. 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.
    13. Mar-Ortiz, Julio & Castillo-García, Norberto & Gracia, María D., 2020. "A decision support system for a capacity management problem at a container terminal," International Journal of Production Economics, Elsevier, vol. 222(C).
    14. Gang Chen & Liping Jiang, 2016. "Managing customer arrivals with time windows: a case of truck arrivals at a congested container terminal," Annals of Operations Research, Springer, vol. 244(2), pages 349-365, September.
    15. Wenrui Qu & Tao Tao & Bo Xie & Yi Qi, 2021. "A State-Dependent Approximation Method for Estimating Truck Queue Length at Marine Terminals," Sustainability, MDPI, vol. 13(5), pages 1-18, March.
    16. Schwarz, Justus Arne & Selinka, Gregor & Stolletz, Raik, 2016. "Performance analysis of time-dependent queueing systems: Survey and classification," Omega, Elsevier, vol. 63(C), pages 170-189.
    17. Azab, Ahmed & Morita, Hiroshi, 2022. "The block relocation problem with appointment scheduling," European Journal of Operational Research, Elsevier, vol. 297(2), pages 680-694.
    18. Xiao, Tingting & Ha, Albert Y., 2018. "Optimal unloading and storage pricing for inbound containers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 210-228.
    19. Bowei Xu & Xiaoyan Liu & Yongsheng Yang & Junjun Li & Octavian Postolache, 2021. "Optimization for a Multi-Constraint Truck Appointment System Considering Morning and Evening Peak Congestion," Sustainability, MDPI, vol. 13(3), pages 1-19, January.
    20. Filip Covic, 2017. "Re-marshalling in automated container yards with terminal appointment systems," Flexible Services and Manufacturing Journal, Springer, vol. 29(3), pages 433-503, December.

    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:proeco:v:141:y:2013:i:1:p:179-188. 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: http://www.elsevier.com/locate/ijpe .

    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.