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Multi-criteria decision-making for complex bundling configurations in surface transportation of air freight

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  • Rezaei, Jafar
  • Hemmes, Alexander
  • Tavasszy, Lori

Abstract

Airlines typically carry out freight transportation in a hub and spoke structure, where the movements between the outstations and the hub are served by trucks. To transport freight efficiently, air carriers must consider bundling options for shipments that are delivered at outstations and have to be moved to the hub. There are three options when it comes to bundling freight: on ‘through unit load devices’ (T-ULD) (all freight for the same flight at the hub), on ‘mixed unit load devices’ (M-ULD) (freight for different flights at the hub) and loose freight in trucks. The optimal freight bundling configuration for carriers, taking into account their main KPIs (key performance indicators), is unknown. This research formulates the problem as a multi-criteria decision-making (MCDM) problem, allowing carriers to decide which configuration is optimal for a given outstation. The selected KPIs (cost, (un)loading time, and quality) are formulated as mathematical functions. A new MCDM, called best worst method (BWM), is then used to identify the best configuration with respect to the three KPIs. The proposed methodology is applied to KLM Cargo to identify the best configuration for the selected outstations that supply freight to the KLM hub at Schiphol Airport. This case study shows that there are different optimal freight bundling configurations for different outstations and that trucking costs and freight handling tariffs are among the key factors in deciding which configuration is optimal.

Suggested Citation

  • Rezaei, Jafar & Hemmes, Alexander & Tavasszy, Lori, 2017. "Multi-criteria decision-making for complex bundling configurations in surface transportation of air freight," Journal of Air Transport Management, Elsevier, vol. 61(C), pages 95-105.
    • Handle: RePEc:eee:jaitra:v:61:y:2017:i:c:p:95-105
    DOI: 10.1016/j.jairtraman.2016.02.006
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