IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i22p9743-d1516654.html
   My bibliography  Save this article

Sustainable Synchronization of Truck Arrival and Yard Crane Scheduling in Container Terminals: An Agent-Based Simulation of Centralized and Decentralized Approaches Considering Carbon Emissions

Author

Listed:
  • Veterina Nosadila Riaventin

    (Industrial Engineering Program, Faculty of Industrial Technology, Bandung Institute of Technology, Bandung 40132, Indonesia
    Research Group of Industrial System and Techno-Economics, Bandung Institute of Technology, Bandung 40132, Indonesia
    Center for Logistics and Supply Chain Studies, Bandung Institute of Technology, Bandung 40132, Indonesia)

  • Andi Cakravastia

    (Industrial Engineering Program, Faculty of Industrial Technology, Bandung Institute of Technology, Bandung 40132, Indonesia
    Research Group of Industrial System and Techno-Economics, Bandung Institute of Technology, Bandung 40132, Indonesia
    Center for Logistics and Supply Chain Studies, Bandung Institute of Technology, Bandung 40132, Indonesia)

  • Rully Tri Cahyono

    (Industrial Engineering Program, Faculty of Industrial Technology, Bandung Institute of Technology, Bandung 40132, Indonesia
    Research Group of Industrial System and Techno-Economics, Bandung Institute of Technology, Bandung 40132, Indonesia
    Center for Logistics and Supply Chain Studies, Bandung Institute of Technology, Bandung 40132, Indonesia)

  • Suprayogi

    (Industrial Engineering Program, Faculty of Industrial Technology, Bandung Institute of Technology, Bandung 40132, Indonesia
    Research Group of Industrial System and Techno-Economics, Bandung Institute of Technology, Bandung 40132, Indonesia
    Center for Logistics and Supply Chain Studies, Bandung Institute of Technology, Bandung 40132, Indonesia)

Abstract

Background: Container terminal congestion is often measured by the average turnaround time for external trucks. Reducing the average turnaround time can be resolved by controlling the yard crane operation and the arrival times of external trucks (truck appointment system). Because the truck appointment system and yard crane scheduling problem are closely interconnected, this research investigates synchronization between the approaches used in truck appointment systems and yard crane scheduling strategies. Rubber-tired gantry (RTG) operators for yard crane scheduling operations strive to reduce RTG movement time as part of the container retrieval service. However, there is a conflict between individual agent goals. While seeking to minimize truck turnaround time, RTGs may travel long distances, ultimately slowing down the RTG service. Methods: We address a method that balances individual agent goals while also considering the collective objective, thereby minimizing turnaround time. An agent-based simulation is proposed to simulate scenarios for yard crane scheduling strategies and truck appointment system approaches, which are centralized and decentralized. This study explores the combined effects of different yard scheduling strategies and truck appointment procedures on performance indicators. Various configurations of the truck appointment system and yard scheduling strategies are modeled to investigate how those factors affect the average turnaround time, yard crane utilization, and CO 2 emissions. Results: At all levels of truck arrival rates, the nearest-truck-first-served (NTFS) scenario tends to provide lower external truck turnaround times than the first-come-first-served (FCFS) and nearest-truck longest-waiting-time first-served (NLFS) scenario. Conclusions: The decentralized truck appointment system (DTAS) generally shows slightly higher efficiency in emission reduction compared with centralized truck appointment system (CTAS), especially at moderate to high truck arrival rates. The decentralized approach of the truck appointment system should be accompanied by the yard scheduling strategy to obtain better performance indicators.

Suggested Citation

  • Veterina Nosadila Riaventin & Andi Cakravastia & Rully Tri Cahyono & Suprayogi, 2024. "Sustainable Synchronization of Truck Arrival and Yard Crane Scheduling in Container Terminals: An Agent-Based Simulation of Centralized and Decentralized Approaches Considering Carbon Emissions," Sustainability, MDPI, vol. 16(22), pages 1-25, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:9743-:d:1516654
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/22/9743/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/22/9743/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhou, Chenhao & Lee, Byung Kwon & Li, Haobin, 2020. "Integrated optimization on yard crane scheduling and vehicle positioning at container yards," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    2. Theo E Notteboom, 2006. "The Time Factor in Liner Shipping Services," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 8(1), pages 19-39, March.
    3. Boysen, Nils & Emde, Simon, 2016. "The parallel stack loading problem to minimize blockages," European Journal of Operational Research, Elsevier, vol. 249(2), pages 618-627.
    4. Boysen, Nils & Emde, Simon, 2016. "The parallel stack loading problem to minimize blockages," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 79433, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. 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.
    6. Yunfeng Gao & Ying-En Ge, 2023. "Integrated scheduling of yard cranes, external trucks, and internal trucks in maritime container terminal operation," Maritime Policy & Management, Taylor & Francis Journals, vol. 50(5), pages 629-650, July.
    7. Kim, Kap Hwan & Lee, Keung Mo & Hwang, Hark, 2003. "Sequencing delivery and receiving operations for yard cranes in port container terminals," International Journal of Production Economics, Elsevier, vol. 84(3), pages 283-292, June.
    8. 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.
    9. 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.
    10. Sanghyuk Yi & Bernd Scholz-Reiter & Taehoon Kim & Kap Hwan Kim, 2019. "Scheduling appointments for container truck arrivals considering their effects on congestion," Flexible Services and Manufacturing Journal, Springer, vol. 31(3), pages 730-762, September.
    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. 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.
    2. 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).
    3. Afef Lagha & Bechir Ben Daya & Jean-François Audy, 2024. "Assessment of Greenhouse Gas Emissions from Heavy-Duty Trucking in a Non-Containerized Port through Simulation-Based Methods," Sustainability, MDPI, vol. 16(5), pages 1-27, February.
    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. Budhi S. Wibowo & Jan C. Fransoo, 2023. "Performance analysis of a drop-swap terminal to mitigate truck congestion at chemical sites," Flexible Services and Manufacturing Journal, Springer, vol. 35(2), pages 416-454, June.
    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. Christina Büsing & Sigrid Knust & Xuan Thanh Le, 2018. "Trade-off between robustness and cost for a storage loading problem: rule-based scenario generation," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 6(4), pages 339-365, December.
    8. Bechir Ben Daya & Jean-François Audy, 2024. "Port Access Fluidity Management during a Major Extension Project: A Simulation-Based Case Study," Sustainability, MDPI, vol. 16(7), pages 1-30, March.
    9. Gharehgozli, Amir & Zaerpour, Nima, 2018. "Stacking outbound barge containers in an automated deep-sea terminal," European Journal of Operational Research, Elsevier, vol. 267(3), pages 977-995.
    10. Frank Gurski & Carolin Rehs & Jochen Rethmann & Egon Wanke, 2019. "Controlling distribution conveyors and multiline palletizers: theoretical foundations and online algorithms," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(2), pages 581-611, June.
    11. 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.
    12. Facchini, F. & Digiesi, S. & Mossa, G., 2020. "Optimal dry port configuration for container terminals: A non-linear model for sustainable decision making," International Journal of Production Economics, Elsevier, vol. 219(C), pages 164-178.
    13. Davies K. Bett & Islam Ali & Mohamed Gheith & Amr Eltawil, 2024. "Simulation-Based Optimization of Truck Appointment Systems in Container Terminals: A Dual Transactions Approach with Improved Congestion Factor Representation," Logistics, MDPI, vol. 8(3), pages 1-30, August.
    14. Damla Kizilay & Deniz Türsel Eliiyi, 2021. "A comprehensive review of quay crane scheduling, yard operations and integrations thereof in container terminals," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 1-42, March.
    15. Gharehgozli, Amir & Yu, Yugang & de Koster, René & Du, Shaofu, 2019. "Sequencing storage and retrieval requests in a container block with multiple open locations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 261-284.
    16. Gharehgozli, Amir Hossein & Vernooij, Floris Gerardus & Zaerpour, Nima, 2017. "A simulation study of the performance of twin automated stacking cranes at a seaport container terminal," European Journal of Operational Research, Elsevier, vol. 261(1), pages 108-128.
    17. Gharehgozli, Amir & Zaerpour, Nima, 2020. "Robot scheduling for pod retrieval in a robotic mobile fulfillment system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    18. Escudero-Santana, Alejandro & Muñuzuri, Jesús & Cortés, Pablo & Onieva, Luis, 2021. "The one container drayage problem with soft time windows," Research in Transportation Economics, Elsevier, vol. 90(C).
    19. Ahmed M. Abdelmagid & Mohamed Gheith & Amr Eltawil, 2022. "Scheduling External Trucks Appointments in Container Terminals to Minimize Cost and Truck Turnaround Times," Logistics, MDPI, vol. 6(3), pages 1-22, July.
    20. Tanaka, Shunji & Tierney, Kevin & Parreño-Torres, Consuelo & Alvarez-Valdes, Ramon & Ruiz, Rubén, 2019. "A branch and bound approach for large pre-marshalling problems," European Journal of Operational Research, Elsevier, vol. 278(1), pages 211-225.

    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:gam:jsusta:v:16:y:2024:i:22:p:9743-:d:1516654. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.