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Optimizing Truck Visits to Container Terminals with Consideration of Multiple Drays of Individual Drivers

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  • Raka Jovanovic

Abstract

In this paper a new approach for designing a truck appointment system (TAS) at container terminals is proposed. While the vast majority of published research analyzes the TAS from the perspective of drayage companies and terminal operations, in this work this topic is centered around truck drivers. The objective of this approach is to show that it is possible to increase the satisfaction of drivers which will maintain the positive effects that the TAS provides to the port. To be more precise, the focus is on exploiting the fact that individual truck drivers perform multiple visits to the container terminal in a day. Based on this information, a scheduling problem is defined and the corresponding integer programming model is developed. The potential benefits of the proposed approach are evaluated for the ports of Los Angeles and the port of Seattle. This has been done by generating problem instances based on the distribution of the number of daily truck visits to the port, number of daily working hours of drivers, and distances (lengths) of individual dray moves for the corresponding ports. The results of the conducted computational experiments show that using the proposed approach can positively affect gate waiting times and truck driver satisfaction. Further, it is shown that this type of approach favors more experienced drivers, which has a potential to provide additional benefits to the port.

Suggested Citation

  • Raka Jovanovic, 2018. "Optimizing Truck Visits to Container Terminals with Consideration of Multiple Drays of Individual Drivers," Journal of Optimization, Hindawi, vol. 2018, pages 1-8, September.
  • Handle: RePEc:hin:jjopti:5165124
    DOI: 10.1155/2018/5165124
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    Cited by:

    1. Orlando Marco Belcore & Massimo Di Gangi & Antonio Polimeni, 2023. "Connected Vehicles and Digital Infrastructures: A Framework for Assessing the Port Efficiency," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    2. 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.

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