Impact of overbooking reservation mechanism on container terminal's operational performance and greenhouse gas emissions

Wasesa Meditya; Ramadhan Fakhri I.; Nita Arfenia; Belgiawan Prawira F.; Mayangsari Lidia

doi:10.1016/j.ajsl.2021.01.002

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자료유형: 학술저널

저자정보: Wasesa Meditya (Bandung Institute of Technology) Ramadhan Fakhri I. (Bandung Institute of Technology) Nita Arfenia (Bandung Institute of Technology) Belgiawan Prawira F. (Bandung Institute of Technology) Mayangsari Lidia (Bandung Institute of Technology)

저널정보: 한국해운물류학회 The Asian Journal of Shipping and Logistics The Asian Journal of Shipping and Logistics Vol.37 No.2

발행연도: 2021.6

수록면: 140 - 148 (9page)

DOI: 10.1016/j.ajsl.2021.01.002

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Truck appointment systems facilitate coordination between container terminals and drayage trucks incontainer pick-up operation reservation. However, in many cases, trucks with a reservation do not arriveat the scheduled appointment. As the number of no-shows increases, the container terminal’s produc-tivity will plummet, and drayage trucks that failed to get reservations will lose their opportunity toget service. This research proposes an overbooking reservation mechanism (ORM) to alleviate the neg-ative impact of these no-shows. This research scrutinizes the detailed process mapping of the existingreservation mechanism, proposes an ORM, and conducts agent-based simulations to evaluate the ORM’sperformance against the regular and go-show reservation mechanisms at different levels of no-showsand working occupancies. The application of an ORM can improve productivity and service levels whileminimizing such negative externalities as queue length, overtime, and greenhouse gas emissions. Highovertime intensities only appear when the container terminal’s workload is exceptionally high, at 200%of maximum capacity, with a low level of no-shows. Even in exceptionally high demand conditions, thedrayage trucks wait only up to 16 min before receiving service.

#Truck appointment system #Overbooking reservation mechanism #Container terminals #Hinterland operation #Agent-based simulation #Greenhouse gas emissions

참고문헌 (29)

참고문헌 신청

Acciaro, M. / 2013 / Efficient hinterland transport infrastructure and services for large container ports / International Transport Forum Discussion Paper 19(1):1~32

Marta Gonzalez Aregall / 2018 / A global review of the hinterland dimension of green port strategies / Transportation Research Part D: Transport and Environment 59:23~34

Claudia Caballini / 2020 / A combined data mining – optimization approach to manage trucks operations in container terminals with the use of a TAS: Application to an Italian and a Mexican port / Transportation Research Part E: Logistics and Transportation Review 142:102054

Gang Chen / 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 55:3~22

Do, N. A. D. / 2016 / A simulation-based genetic algorithm approach for reducing emissions from import container pick-up operation at container terminal / Annals of Operations Research 242(2):285~301

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