IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v179y2024ics0191261523001996.html
   My bibliography  Save this article

Dynamic container slot allocation for a liner shipping service

Author

Listed:
  • Wang, Tingsong
  • Meng, Qiang
  • Tian, Xuecheng

Abstract

In this paper, we study a dynamic container slot allocation problem (DCSAP) for a liner container shipping company that aims to make an acceptance or rejection decision to each dynamically arriving container slot booking request. To capture the dynamic arrival feature and real-time acceptance/rejection decision of the booking request, we formulate the DCSAP as a dynamic programming (DP) model with the objective of maximizing the total revenues generated by accepted container booking requests over the entire booking horizon. Due to the well-known curse of dimensionality of solving a DP model, we develop a series of models to transform the intractable DP model into a solvable approximate linear programming (ALP) model. We further propose a spatiotemporal-heterogeneity-based (STH-based) decomposition preprocessor by identifying the spatiotemporal property of the DCSAP before solving the ALP model. Extensive numerical experiments are conducted to assess the applicability of the developed research methodology.

Suggested Citation

  • Wang, Tingsong & Meng, Qiang & Tian, Xuecheng, 2024. "Dynamic container slot allocation for a liner shipping service," Transportation Research Part B: Methodological, Elsevier, vol. 179(C).
    • Handle: RePEc:eee:transb:v:179:y:2024:i:c:s0191261523001996
    DOI: 10.1016/j.trb.2023.102874
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191261523001996
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.trb.2023.102874?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. Bell, Michael G.H. & Liu, Xin & Rioult, Jeremy & Angeloudis, Panagiotis, 2013. "A cost-based maritime container assignment model," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 58-70.
    2. William L. Cooper, 2002. "Asymptotic Behavior of an Allocation Policy for Revenue Management," Operations Research, INFORMS, vol. 50(4), pages 720-727, August.
    3. Dan Zhang & Larry Weatherford, 2017. "Dynamic Pricing for Network Revenue Management: A New Approach and Application in the Hotel Industry," INFORMS Journal on Computing, INFORMS, vol. 29(1), pages 18-35, February.
    4. Pillac, Victor & Gendreau, Michel & Guéret, Christelle & Medaglia, Andrés L., 2013. "A review of dynamic vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 225(1), pages 1-11.
    5. Daniel Adelman, 2007. "Dynamic Bid Prices in Revenue Management," Operations Research, INFORMS, vol. 55(4), pages 647-661, August.
    6. A. Ciancimino & G. Inzerillo & S. Lucidi & L. Palagi, 1999. "A Mathematical Programming Approach for the Solution of the Railway Yield Management Problem," Transportation Science, INFORMS, vol. 33(2), pages 168-181, May.
    7. Liang, Jinpeng & Li, Liming & Zheng, Jianfeng & Tan, Zhijia, 2023. "Service-oriented container slot allocation policy under stochastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 176(C).
    8. Dimitris Bertsimas & Ioana Popescu, 2003. "Revenue Management in a Dynamic Network Environment," Transportation Science, INFORMS, vol. 37(3), pages 257-277, August.
    9. Shin-Chan Ting * & Gwo-Hshiung Tzeng, 2004. "An optimal containership slot allocation for liner shipping revenue management," Maritime Policy & Management, Taylor & Francis Journals, vol. 31(3), pages 199-211, July.
    10. Wen He & Lawrence C. Leung & Yer Van Hui & Gang Chen, 2019. "An air freight forwarder’s resource planning and revenue management," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(2), pages 294-309, February.
    11. George B. Dantzig & Philip Wolfe, 1960. "Decomposition Principle for Linear Programs," Operations Research, INFORMS, vol. 8(1), pages 101-111, February.
    12. L.H. Lee & E.P. Chew & M.S. Sim, 2009. "A revenue management model for sea cargo," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 6(2), pages 195-222.
    13. Thomas W. M. Vossen & Dan Zhang, 2015. "Reductions of Approximate Linear Programs for Network Revenue Management," Operations Research, INFORMS, vol. 63(6), pages 1352-1371, December.
    14. Huseyin Topaloglu, 2009. "Using Lagrangian Relaxation to Compute Capacity-Dependent Bid Prices in Network Revenue Management," Operations Research, INFORMS, vol. 57(3), pages 637-649, June.
    15. Wang, Yadong & Meng, Qiang & Du, Yuquan, 2015. "Liner container seasonal shipping revenue management," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 141-161.
    16. D. P. de Farias & B. Van Roy, 2003. "The Linear Programming Approach to Approximate Dynamic Programming," Operations Research, INFORMS, vol. 51(6), pages 850-865, December.
    17. Wang, Tingsong & Meng, Qiang & Wang, Shuaian & Qu, Xiaobo, 2021. "A two-stage stochastic nonlinear integer-programming model for slot allocation of a liner container shipping service," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 143-160.
    18. Wang, Tingsong & Tian, Xuecheng & Wang, Yadong, 2020. "Container slot allocation and dynamic pricing of time-sensitive cargoes considering port congestion and uncertain demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    19. Meng, Qiang & Wang, Tingsong & Wang, Shuaian, 2012. "Short-term liner ship fleet planning with container transshipment and uncertain container shipment demand," European Journal of Operational Research, Elsevier, vol. 223(1), pages 96-105.
    20. Meng, Qiang & Zhao, Hui & Wang, Yadong, 2019. "Revenue management for container liner shipping services: Critical review and future research directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 280-292.
    21. Wang, Shuaian & Liu, Zhiyuan & Bell, Michael G.H., 2015. "Profit-based maritime container assignment models for liner shipping networks," Transportation Research Part B: Methodological, Elsevier, vol. 72(C), pages 59-76.
    22. Kalyan Talluri & Garrett van Ryzin, 2004. "Revenue Management Under a General Discrete Choice Model of Consumer Behavior," Management Science, INFORMS, vol. 50(1), pages 15-33, January.
    23. Sumit Kunnumkal & Kalyan Talluri, 2011. "Equivalence of Piecewise-Linear Approximation and Lagrangian Relaxation for Network Revenue Management," Working Papers 608, Barcelona School of Economics.
    24. Kalyan Talluri & Garrett van Ryzin, 1998. "An Analysis of Bid-Price Controls for Network Revenue Management," Management Science, INFORMS, vol. 44(11-Part-1), pages 1577-1593, November.
    25. A. Charnes & W. W. Cooper & K. Kortanek, 1963. "Duality in Semi-Infinite Programs and Some Works of Haar and Carathéodory," Management Science, INFORMS, vol. 9(2), pages 209-228, January.
    26. Thomas W. M. Vossen & Dan Zhang, 2015. "A Dynamic Disaggregation Approach to Approximate Linear Programs for Network Revenue Management," Production and Operations Management, Production and Operations Management Society, vol. 24(3), pages 469-487, March.
    27. Bell, Michael G.H. & Liu, Xin & Angeloudis, Panagiotis & Fonzone, Achille & Hosseinloo, Solmaz Haji, 2011. "A frequency-based maritime container assignment model," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1152-1161, September.
    28. Wang, Xinchang, 2016. "Stochastic resource allocation for containerized cargo transportation networks when capacities are uncertain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 334-357.
    29. Aydin, N. & Birbil, S.I., 2018. "Decomposition methods for dynamic room allocation in hotel revenue management," European Journal of Operational Research, Elsevier, vol. 271(1), pages 179-192.
    30. Chaoxu Tong & Huseyin Topaloglu, 2014. "On the Approximate Linear Programming Approach for Network Revenue Management Problems," INFORMS Journal on Computing, INFORMS, vol. 26(1), pages 121-134, February.
    31. Wang, Tingsong & Xing, Zheng & Hu, Hongtao & Qu, Xiaobo, 2019. "Overbooking and delivery-delay-allowed strategies for container slot allocation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 433-447.
    32. Jacques Desrosiers & Marco E. Lübbecke, 2005. "A Primer in Column Generation," Springer Books, in: Guy Desaulniers & Jacques Desrosiers & Marius M. Solomon (ed.), Column Generation, chapter 0, pages 1-32, Springer.
    33. Sebastian Zurheide & Kathrin Fischer, 2012. "A revenue management slot allocation model for liner shipping networks," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 14(3), pages 334-361, September.
    34. Dimitris Bertsimas & Sanne de Boer, 2005. "Simulation-Based Booking Limits for Airline Revenue Management," Operations Research, INFORMS, vol. 53(1), pages 90-106, February.
    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. Thomas W. M. Vossen & Dan Zhang, 2015. "Reductions of Approximate Linear Programs for Network Revenue Management," Operations Research, INFORMS, vol. 63(6), pages 1352-1371, December.
    2. Wang, Tingsong & Meng, Qiang & Wang, Shuaian & Qu, Xiaobo, 2021. "A two-stage stochastic nonlinear integer-programming model for slot allocation of a liner container shipping service," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 143-160.
    3. Laumer, Simon & Barz, Christiane, 2023. "Reductions of non-separable approximate linear programs for network revenue management," European Journal of Operational Research, Elsevier, vol. 309(1), pages 252-270.
    4. Liang, Jinpeng & Li, Liming & Zheng, Jianfeng & Tan, Zhijia, 2023. "Service-oriented container slot allocation policy under stochastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 176(C).
    5. Wang, Tingsong & Tian, Xuecheng & Wang, Yadong, 2020. "Container slot allocation and dynamic pricing of time-sensitive cargoes considering port congestion and uncertain demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 144(C).
    6. Meng, Qiang & Zhao, Hui & Wang, Yadong, 2019. "Revenue management for container liner shipping services: Critical review and future research directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 280-292.
    7. Georgia Perakis & Guillaume Roels, 2010. "Robust Controls for Network Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 12(1), pages 56-76, November.
    8. Wuyang Yuan & Lei Nie & Xin Wu & Huiling Fu, 2018. "A dynamic bid price approach for the seat inventory control problem in railway networks with consideration of passenger transfer," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-23, August.
    9. Wang, Yadong & Gu, Yuyun & Wang, Tingsong & Zhang, Jun, 2022. "A risk-averse approach for joint contract selection and slot allocation in liner container shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    10. Dan Zhang, 2011. "An Improved Dynamic Programming Decomposition Approach for Network Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 13(1), pages 35-52, April.
    11. Sun, Qinghe & Li, Wei & Meng, Qiang, 2024. "Single-leg shipping revenue management for expedited services with ambiguous elasticity in transit-time-sensitive demand," Transportation Research Part B: Methodological, Elsevier, vol. 180(C).
    12. Xiang Zhao & Xinghua Shan & Jinfei Wu, 2023. "The Impact of Seat Resource Fragmentation on Railway Network Revenue Management," Networks and Spatial Economics, Springer, vol. 23(1), pages 135-177, March.
    13. Ş. İlker Birbil & J. B. G. Frenk & Joaquim A. S. Gromicho & Shuzhong Zhang, 2014. "A Network Airline Revenue Management Framework Based on Decomposition by Origins and Destinations," Transportation Science, INFORMS, vol. 48(3), pages 313-333, August.
    14. Wang, Xinchang & Wang, Hua & Zhang, Xiaoning, 2016. "Stochastic seat allocation models for passenger rail transportation under customer choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 95-112.
    15. Moussawi-Haidar, Lama & Nasr, Walid & Jalloul, Maya, 2021. "Standardized cargo network revenue management with dual channels under stochastic and time-dependent demand," European Journal of Operational Research, Elsevier, vol. 295(1), pages 275-291.
    16. Yuhang Ma & Paat Rusmevichientong & Mika Sumida & Huseyin Topaloglu, 2020. "An Approximation Algorithm for Network Revenue Management Under Nonstationary Arrivals," Operations Research, INFORMS, vol. 68(3), pages 834-855, May.
    17. Haque, Md Tabish & Hamid, Faiz, 2023. "Social distancing and revenue management—A post-pandemic adaptation for railways," Omega, Elsevier, vol. 114(C).
    18. Mika Sumida & Huseyin Topaloglu, 2019. "An Approximation Algorithm for Capacity Allocation Over a Single Flight Leg with Fare-Locking," INFORMS Journal on Computing, INFORMS, vol. 31(1), pages 83-99, February.
    19. Hossein Jahandideh & Julie Ward Drew & Filippo Balestrieri & Kevin McCardle, 2020. "Individualized Pricing for a Cloud Provider Hosting Interactive Applications," Service Science, INFORMS, vol. 12(4), pages 130-147, December.
    20. Daniel Adelman, 2007. "Dynamic Bid Prices in Revenue Management," Operations Research, INFORMS, vol. 55(4), pages 647-661, August.

    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:transb:v:179:y:2024:i:c:s0191261523001996. 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/wps/find/journaldescription.cws_home/548/description#description .

    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.