A novel data-driven engine for identifying trailer capacity sharing opportunities during shipment planning stages is developed for providing a practical solution for collaborative freight logistics. The engine is based on a novel trailer capacity graph (TCG) that describes the real-time trailer capacity status of all collaborating partners. Compared with previous methods that replying on OD of shipments and trailer trips, the application of a TCG enables this engine to match shipments with both the OD and the route of trailer trips. Moreover, special treatments of a TCG, namely trailer route approximation and route shape simplification, dramatically reduce the computational cost, which makes this engine extendable for serving more than two collaborating partners in real-time. Experiments using this engine based on real-world data provided by two companies first illustrate that users of this engine should be aware that the configuration of the treatments of TCG is a trade-off between computational performance and effectiveness in identifying opportunities. Secondly, experiment results suggest that this two-partners collaboration implies an imbalance favourable towards the smaller operator. However, this unfavourable imbalance for the larger operator is likely to reduce as the number of operators joining the collaboration increases.
|Title of host publication||Transport Research Board Annual Meeting 2020|
|Publisher||The National Academy of Sciences of the United States of America|
|Publication status||Published - 2020|
|Event||Transportation Research Board (TRB) 99th Annual Meeting 2020 - Washington DC, Washington DC, United States|
Duration: 12 Jan 2020 → 16 Jan 2020
|Conference||Transportation Research Board (TRB) 99th Annual Meeting 2020|
|Period||12/01/2020 → 16/01/2020|