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Terminal appointment system design by non-stationary M(t)/Ek/c(t) queueing model and genetic algorithm

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  • Chen, Gang
  • Govindan, Kannan
  • Yang, Zhong-Zhen
  • Choi, Tsan-Ming
  • Jiang, Liping

Abstract

Long truck queue is a common problem at big marine container terminals, where the resources and equipment are usually scheduled to serve ships prior to trucks. To reduce truck queues, some container terminals adopt terminal appointment system (TAS) to manage truck arrivals. This paper addresses two implementation scenarios of TAS: static TAS (STAS) and dynamic TAS (DTAS). First, a non-stationary M(t)/Ek/c(t) queueing model is used to analyse a terminal gate system, and solved with a new approximation approach. Then, genetic algorithm is applied to optimise the hourly quota of entry appointments in STAS for the derived queueing model. Lastly to relax the assumption of knowing the truckers' preferred arrival pattern in STAS, we propose the concept of DTAS, which is much easier to apply and can assist individual trucker in making appointment by providing real-time estimation of waiting time based on existing appointments. Our analysis reveals DTAS can significantly increase the system flexibility.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:proeco:v:146:y:2013:i:2:p:694-703
    DOI: 10.1016/j.ijpe.2013.09.001
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    Cited by:

    1. 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).
    2. 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).
    3. Nanxi Wang & Daofang Chang & Xiaowei Shi & Jun Yuan & Yinping Gao, 2019. "Analysis and Design of Typical Automated Container Terminals Layout Considering Carbon Emissions," Sustainability, MDPI, vol. 11(10), pages 1-40, May.
    4. Hu, Lu & Zhao, Bin & Zhu, Juanxiu & Jiang, Yangsheng, 2019. "Two time-varying and state-dependent fluid queuing models for traffic circulation systems," European Journal of Operational Research, Elsevier, vol. 275(3), pages 997-1019.
    5. 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.
    6. 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).
    7. 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.
    8. Azab, Ahmed & Morita, Hiroshi, 2022. "The block relocation problem with appointment scheduling," European Journal of Operational Research, Elsevier, vol. 297(2), pages 680-694.
    9. Marina Zanne & Elen Twrdy & Bojan Beškovnik, 2021. "The Effect of Port Gate Location and Gate Procedures on the Port-City Relation," Sustainability, MDPI, vol. 13(9), pages 1-22, April.
    10. 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.
    11. Dhingra, Vibhuti & Kumawat, Govind Lal & Roy, Debjit & Koster, René de, 2018. "Solving semi-open queuing networks with time-varying arrivals: An application in container terminal landside operations," European Journal of Operational Research, Elsevier, vol. 267(3), pages 855-876.
    12. Sazvar, Z. & Mirzapour Al-e-hashem, S.M.J. & Govindan, K. & Bahli, B., 2016. "A novel mathematical model for a multi-period, multi-product optimal ordering problem considering expiry dates in a FEFO system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 232-261.
    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. 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.
    15. Ngoc Anh Dung Do & Izabela Ewa Nielsen & Gang Chen & Peter Nielsen, 2016. "A simulation-based genetic algorithm approach for reducing emissions from import container pick-up operation at container terminal," Annals of Operations Research, Springer, vol. 242(2), pages 285-301, July.
    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. 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.
    18. 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.
    19. 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.
    20. Kannan Govindan, 2016. "Evolutionary algorithms for supply chain management," Annals of Operations Research, Springer, vol. 242(2), pages 195-206, July.

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