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Truck Scheduling Problem Considering Carbon Emissions under Truck Appointment System

Author

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  • Houming Fan

    (Transportation Engineering, Dalian Maritime University, Dalian 116026, China
    Institute of Strategy Management and System Planning, Dalian 116026, China)

  • Xiaoxue Ren

    (Transportation Engineering, Dalian Maritime University, Dalian 116026, China
    Institute of Strategy Management and System Planning, Dalian 116026, China)

  • Zhenfeng Guo

    (Transportation Engineering, Dalian Maritime University, Dalian 116026, China)

  • Yang Li

    (School of Mining Engineering, Liaoning Shihua University, Fushun 113005, China)

Abstract

Aiming at the truck scheduling problem between the outer yard and multi-terminals, the appointment optimization model of truck is established. In this model, the queue time and the operation time of truck during the appointment period of different terminals are different. Under the restriction of given appointment quotas of each appointment period, determine the arrival amount of trucks in each appointment period. The goal is to reduce carbon emissions and total costs, improve the efficiency of truck scheduling. To solve this model, hybrid genetic algorithm with variable neighborhood search was designed. Firstly, generate chromosomes, and the front part of the chromosome represents the demand for 40 ft containers and the back part represents the demand for 20 ft containers. Then, the route is generated according to the time constraint and appointment quotas of each appointment period. Finally, the neighborhood search strategy is adopted to improve the solution quality. The validity of the model and algorithm were verified by an example. A low-carbon scheduling scheme was obtained under truck appointment system. The results show that the scheduling scheme under truck appointment system uses fewer trucks, improves the efficiency of delivery, reduces the total costs, and it takes into account the requirements of low carbon.

Suggested Citation

  • Houming Fan & Xiaoxue Ren & Zhenfeng Guo & Yang Li, 2019. "Truck Scheduling Problem Considering Carbon Emissions under Truck Appointment System," Sustainability, MDPI, vol. 11(22), pages 1-23, November.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:22:p:6256-:d:284652
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    References listed on IDEAS

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    Cited by:

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    2. 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.
    3. Neven Grubisic & Tomislav Krljan & Livia Maglić & Siniša Vilke, 2020. "The Microsimulation Model for Assessing the Impact of Inbound Traffic Flows for Container Terminals Located near City Centers," Sustainability, MDPI, vol. 12(22), pages 1-19, November.
    4. 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.
    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. Zhihong Jin & Xin Lin & Linlin Zang & Weiwei Liu & Xisheng Xiao, 2021. "Lane Allocation Optimization in Container Seaport Gate System Considering Carbon Emissions," Sustainability, MDPI, vol. 13(7), pages 1-16, March.

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