IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v297y2022i2p680-694.html
   My bibliography  Save this article

The block relocation problem with appointment scheduling

Author

Listed:
  • Azab, Ahmed
  • Morita, Hiroshi

Abstract

In many container terminals, containers are piled vertically and horizontally in the terminal yard, limited mainly by the dimensions of the yard crane. Import and export containers are typically stacked separately. An external truck can access the terminal to pick up an import container only after making an appointment reserving a pickup time. To reduce truck waiting time inside the terminal, container pickup appointments are normally scheduled on a time window basis. However, when a truck arrives at the terminal yard at the appointed time, it is common for the target container not to be at the top of its stack, resulting in unproductive relocations to remove all the containers stacked above the target container and thus increasing the truck's waiting time. To minimize the number of relocations, the Block Relocation Problem (BRP) is usually solved independently, without consideration of appointment scheduling. In this paper, we introduce a new optimization problem—the Block Relocation Problem with Appointment Scheduling (BRPAS)—to jointly address the two issues. To solve the problem, two binary IP models are proposed, and examples from the literature are solved to confirm the performance of the two models. The proposed formulations are further extended to cover several operational aspects related to the flexibility of container pickup operations. Results show that the proposed approach can improve container relocation operations at terminal yards by coordinating with appointment scheduling.

Suggested Citation

  • Azab, Ahmed & Morita, Hiroshi, 2022. "The block relocation problem with appointment scheduling," European Journal of Operational Research, Elsevier, vol. 297(2), pages 680-694.
  • Handle: RePEc:eee:ejores:v:297:y:2022:i:2:p:680-694
    DOI: 10.1016/j.ejor.2021.06.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221721005130
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2021.06.007?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. 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.
    3. Petering, Matthew E.H. & Hussein, Mazen I., 2013. "A new mixed integer program and extended look-ahead heuristic algorithm for the block relocation problem," European Journal of Operational Research, Elsevier, vol. 231(1), pages 120-130.
    4. 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.
    5. 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.
    6. 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.
    7. Phan, Mai-Ha & Kim, Kap Hwan, 2016. "Collaborative truck scheduling and appointments for trucking companies and container terminals," Transportation Research Part B: Methodological, Elsevier, vol. 86(C), pages 37-50.
    8. Yat‐wah Wan & Jiyin Liu & Pei‐Chun Tsai, 2009. "The assignment of storage locations to containers for a container stack," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(8), pages 699-713, December.
    9. Galle, Virgile & Barnhart, Cynthia & Jaillet, Patrick, 2018. "A new binary formulation of the restricted Container Relocation Problem based on a binary encoding of configurations," European Journal of Operational Research, Elsevier, vol. 267(2), pages 467-477.
    10. 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.
    11. Bacci, Tiziano & Mattia, Sara & Ventura, Paolo, 2020. "A branch-and-cut algorithm for the restricted Block Relocation Problem," European Journal of Operational Research, Elsevier, vol. 287(2), pages 452-459.
    12. Caserta, Marco & Schwarze, Silvia & Voß, Stefan, 2012. "A mathematical formulation and complexity considerations for the blocks relocation problem," European Journal of Operational Research, Elsevier, vol. 219(1), pages 96-104.
    13. 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.
    14. Galle, Virgile & Barnhart, Cynthia & Jaillet, Patrick, 2018. "Yard Crane Scheduling for container storage, retrieval, and relocation," European Journal of Operational Research, Elsevier, vol. 271(1), pages 288-316.
    15. 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.
    16. 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.
    17. 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.
    18. Mengzhi Ma & Houming Fan & Xiaodan Jiang & Zhenfeng Guo, 2019. "Truck Arrivals Scheduling with Vessel Dependent Time Windows to Reduce Carbon Emissions," Sustainability, MDPI, vol. 11(22), pages 1-26, November.
    19. 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.
    20. 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.
    21. Adrián Ramírez-Nafarrate & Rosa G. González-Ramírez & Neale R. Smith & Roberto Guerra-Olivares & Stefan Voß, 2017. "Impact on yard efficiency of a truck appointment system for a port terminal," Annals of Operations Research, Springer, vol. 258(2), pages 195-216, November.
    22. 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.
    23. Tanaka, Shunji & Voß, Stefan, 2019. "An exact algorithm for the block relocation problem with a stowage plan," European Journal of Operational Research, Elsevier, vol. 279(3), pages 767-781.
    24. 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.
    25. 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.
    26. Shiri, Samaneh & Huynh, Nathan, 2016. "Optimization of drayage operations with time-window constraints," International Journal of Production Economics, Elsevier, vol. 176(C), pages 7-20.
    27. Silva, Marcos de Melo da & Erdoğan, Güneş & Battarra, Maria & Strusevich, Vitaly, 2018. "The Block Retrieval Problem," European Journal of Operational Research, Elsevier, vol. 265(3), pages 931-950.
    28. Na Li & Gang Chen & Manwo Ng & Wayne K. Talley & Zhihong Jin, 2020. "Optimized appointment scheduling for export container deliveries at marine terminals," Maritime Policy & Management, Taylor & Francis Journals, vol. 47(4), pages 456-478, June.
    29. Zhang, Canrong & Guan, Hao & Yuan, Yifei & Chen, Weiwei & Wu, Tao, 2020. "Machine learning-driven algorithms for the container relocation problem," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 102-131.
    30. Ji, Mingjun & Guo, Wenwen & Zhu, Huiling & Yang, Yongzhi, 2015. "Optimization of loading sequence and rehandling strategy for multi-quay crane operations in container terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 80(C), pages 1-19.
    31. 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.
    32. Zehendner, Elisabeth & Caserta, Marco & Feillet, Dominique & Schwarze, Silvia & Voß, Stefan, 2015. "An improved mathematical formulation for the blocks relocation problem," European Journal of Operational Research, Elsevier, vol. 245(2), pages 415-422.
    33. 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.
    34. 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.
    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. Azab, Ahmed & Morita, Hiroshi, 2022. "Coordinating truck appointments with container relocations and retrievals in container terminals under partial appointments information," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    2. Roy, Debjit & van Ommeren, Jan-Kees & de Koster, René & Gharehgozli, Amir, 2022. "Modeling landside container terminal queues: Exact analysis and approximations," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 73-102.
    3. 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.
    4. Feng, Yuanjun & Song, Dong-Ping & Li, Dong & Xie, Ying, 2022. "Service fairness and value of customer information for the stochastic container relocation problem under flexible service policy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    5. 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.

    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. Azab, Ahmed & Morita, Hiroshi, 2022. "Coordinating truck appointments with container relocations and retrievals in container terminals under partial appointments information," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    2. Jin, Bo & Tanaka, Shunji, 2023. "An exact algorithm for the unrestricted container relocation problem with new lower bounds and dominance rules," European Journal of Operational Research, Elsevier, vol. 304(2), pages 494-514.
    3. Feng, Yuanjun & Song, Dong-Ping & Li, Dong & Xie, Ying, 2022. "Service fairness and value of customer information for the stochastic container relocation problem under flexible service policy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    4. 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.
    5. Tanaka, Shunji & Voß, Stefan, 2022. "An exact approach to the restricted block relocation problem based on a new integer programming formulation," European Journal of Operational Research, Elsevier, vol. 296(2), pages 485-503.
    6. Tanaka, Shunji & Voß, Stefan, 2019. "An exact algorithm for the block relocation problem with a stowage plan," European Journal of Operational Research, Elsevier, vol. 279(3), pages 767-781.
    7. 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.
    8. 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.
    9. 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).
    10. 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.
    11. Lange, Ann-Kathrin & Kreuz, Felix & Langkau, Sven & Jahn, Carlos & Clausen, Uwe, 2020. "Defining the quota of truck appointment systems," 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 211-246, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    12. 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.
    13. 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.
    14. 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).
    15. Huiling Zhu & Mingjun Ji & Wenwen Guo & Qingbin Wang & Yongzhi Yang, 2019. "Mathematical formulation and heuristic algorithm for the block relocation and loading problem," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(4), pages 333-351, June.
    16. 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.
    17. 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.
    18. Andresson Silva Firmino & Ricardo Martins Abreu Silva & Valéria Cesário Times, 2019. "A reactive GRASP metaheuristic for the container retrieval problem to reduce crane’s working time," Journal of Heuristics, Springer, vol. 25(2), pages 141-173, April.
    19. 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.
    20. 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.

    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:ejores:v:297:y:2022:i:2:p:680-694. 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/eor .

    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.