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Title: Crowd-Shipping: Assessing Alternative Operational Models using the Vehicle Routing Problem with Occasional Drivers
Accession Number: 01697571
Record Type: Component
Abstract: Last mile delivery is challenging for delivery companies. The new concept of “crowd-shipping” could be a good complementary approach for companies to reduce last mile delivery cost. Some companies with physical stores can benefit from crowd-shipping by implementing “in-store customers”. Other companies do not have physical stores, so the occasional driver should pick up orders from the depot, which imposes an additional cost of operation. This paper explores the effect of this additional cost by formulating and solving the vehicle routing problem with occasional drivers. Multiple delivery policy for occasional drivers is also investigated. To incorporate the randomness of origin and destination of occasional drivers a stochastic analysis was conducted. Although, it seems that the additional cost would decrease the benefits of companies without physical stores, it is demonstrated that they can still substantially reduce the last mile delivery cost by implementing crowd-shipping. Companies can increase the reliability of last mile delivery operation cost by attracting more occasional drivers and adopting a multiple delivery policy. Finally, this paper shows the reliability of last mile delivery operation cost increases when the origins of occasional drivers are not at the depot.
Supplemental Notes: This paper was sponsored by TRB committee AT015 Standing Committee on Freight Transportation Planning and Logistics.
Report/Paper Numbers: 19-04948
Language: English
Corporate Authors: Transportation Research BoardAuthors: Mousavi, KianoushSoldouz, Sina ARoorda, Matthew JPagination: 5p
Publication Date: 2019
Conference:
Transportation Research Board 98th Annual Meeting
Location:
Washington DC, United States Media Type: Digital/other
Features: Figures; References
TRT Terms: Uncontrolled Terms: Subject Areas: Freight Transportation; Operations and Traffic Management; Planning and Forecasting
Source Data: Transportation Research Board Annual Meeting 2019 Paper #19-04948
Files: TRIS, TRB, ATRI
Created Date: Dec 7 2018 9:31AM
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