Delivery systems with crowd‐sourced drivers: A pickup and delivery problem with transfers
Co-authored with Afonso Sampaio, Martin Savelsbergh and Luuk Veelenturf is now published in Networks. You can access the full paper in open access here.
Rapid urban growth, the increasing importance of e‐commerce and high consumer service expectations have given rise to new and innovative models for freight delivery within urban environments. Crowdsourced solutions—where drivers are not employed by a carrier but occasionally offer their services through on‐line platforms and are contracted as required by carriers—are receiving growing attention from industry.
We consider a crowdsourced system where drivers express their availability to perform delivery tasks for a given period of time and the platform communicates a schedule with requests to serve. We investigate the potential benefits of introducing transfers to support driver activities. At transfer locations, drivers can drop off packages for pick up by other drivers at a later time. We frame the problem as a multidepot pickup and delivery problem with time windows and transfers, and propose an adaptive large neighborhood search algorithm that effectively identifies beneficial transfer opportunities and synchronizes driver operations.
Computational experiments indicate that introducing transfer options can significantly reduce system‐wide travel distance as well as the number of drivers required to serve a given set of requests, especially when drivers have short availability and requests have high service requirements.
We are currently modifying our algorithms for use in dynamic environments, where requests appear throughout the operating period and (some of the) drivers may also enter and leave the system during the operating period, as this better reflects real‐life settings.
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