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Analysis and Optimization Methods for Centralized Processing of Chassis

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  • Chassiakos, Anastasios
  • Jula, Hossein
  • VanderBeek, Timothy
  • Shellhammer, Matt
  • An, Samnang Dona

Abstract

The twin ports of Long Beach (POLB) and Los Angeles (POLA), consisting of fourteen individually gated terminals, combine to create the largest container port complex in the US. In 2015, the combined ports handled 15.4 million 20-foot equivalent units (TEUs), a 56% increase since 2000, expected to grow higher in the future. This large number of containers and the associated trips to/from the ports, result in traffic congestion, noise pollution, and greenhouse gas emissions in the vicinity of the ports. The current project studies the concept of “Centralized Processing of Chassis,” and the possibility of using it to mitigate some of these problems. This concept revolves around an off-dock terminal (or several off-dock terminals), referred to as Chassis Processing Facilities (CPFs). A CPF is located close to the port, where trucks will go to exchange chassis, thereby reducing traffic at the marine terminals, resulting in reduced travel times and reduced congestion. The current project develops the required analytical framework for modeling and optimization of the CPF use. The developed analytical model is applied to a case study in the Los Angeles/Long Beach port area. The case study identifies sixteen locations in the vicinity of the ports that can be potentially used as CPFs, and examines several scenarios of container pickup/drop-off transactions. The study presents comparisons between the case when chassis exchanges occur at the CPFs versus the case when chassis exchanges occur at the marine terminals. It is shown that a reduction of up to 20% in total travel time can be achieved when using the CPFs, as compared to using only the marine terminals. The study also shows that using up to three of the potential sixteen CPFs provides significant improvements to total travel time, but using more than three CPFs will have insignificant additional benefits. Moreover, a discrete event simulation model is developed and used for detailed simulation scenarios, as well as for examining and evaluating the performance of heuristic methods. View the NCST Project Webpage

Suggested Citation

  • Chassiakos, Anastasios & Jula, Hossein & VanderBeek, Timothy & Shellhammer, Matt & An, Samnang Dona, 2017. "Analysis and Optimization Methods for Centralized Processing of Chassis," Institute of Transportation Studies, Working Paper Series qt1t75c3vw, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt1t75c3vw
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    References listed on IDEAS

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    1. Le-Griffin, Hanh D. & Mai, Lam & Griffin, Mark, 2011. "Impact of container chassis management practices in the United States on terminal operational efficiency: An operations and mitigation policy analysis," Research in Transportation Economics, Elsevier, vol. 32(1), pages 90-99.
    2. Vis, Iris F. A. & de Koster, Rene, 2003. "Transshipment of containers at a container terminal: An overview," European Journal of Operational Research, Elsevier, vol. 147(1), pages 1-16, May.
    3. Jula, Hossein & Chassiakos, Anastasios & Ioannou, Petros, 2006. "Port dynamic empty container reuse," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 42(1), pages 43-60, January.
    4. Notteboom Theo E., 2004. "Container Shipping And Ports: An Overview," Review of Network Economics, De Gruyter, vol. 3(2), pages 1-21, June.
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    Cited by:

    1. Ted Gifford & Robert Gremley, 2019. "Chassis Leasing and Selection Policy for Port Operations," Interfaces, INFORMS, vol. 49(4), pages 239-248, July.
    2. Chassiakos, Anastasios & Jula, Hossein & VanderBeek, Timothy, 2018. "Dynamic Scheduling of Chassis Movements with Chassis Processing Facilities in the Loop," Institute of Transportation Studies, Working Paper Series qt1gt9w6wc, Institute of Transportation Studies, UC Davis.

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