Appointments at container terminals are an effective way to relieve congestion. In order to adjust the truck’s arrival time at the gate, concerning the cooperation and the time window adjustment mode among external trucking companies and terminal operators in the truck appointment system (TAS), the centralized and decentralized dynamic collaborative TAS model are established respectively by mixed integer programming (MIP). Numerical experiments are performed to validate the approach in this study. The results show that the dynamic collaborative TAS can significantly reduce the waiting and congestion costs of the external trucking companies, and better stagger the peak time windows, so as to maximize the synergy between terminal operators and trucking companies. Finally, optimization measures for the scheduled arrival of external trucks outside the container terminal are put forward.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    The Collaborative Scheduling Optimization of External Truck at Container Terminals Based on Mixed Integer Programming under Appointments System


    Beteiligte:
    Xia, Xinhai (Autor:in) / Peng, Zhimin (Autor:in) / Yang, Shuying (Autor:in) / Yang, Jingshan (Autor:in)

    Kongress:

    22nd COTA International Conference of Transportation Professionals ; 2022 ; Changsha, Hunan Province, China


    Erschienen in:

    CICTP 2022 ; 1400-1412


    Erscheinungsdatum :

    08.09.2022




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Optimization of truck appointments in container terminals

    Zhang, Xiaoju / Zeng, Qingcheng / Yang, Zhongzhen | Springer Verlag | 2018


    Scheduling External Trucks Appointments in Container Terminals to Minimize Cost and Truck Turnaround Times

    Ahmed M. Abdelmagid / Mohamed Gheith / Amr Eltawil | DOAJ | 2022

    Freier Zugriff

    Truck Scheduling Optimization of Container Terminals Based on Reservation Feedback

    Ye, Xiaofei / Yang, Chang / Liu, Wenli et al. | ASCE | 2019