Accepted: A choice-based optimization framework for crowdsourced last-mile delivery
I am pleased to announce that our latest paper, "A choice-based optimization framework for crowdsourced last-mile delivery", has been accepted for publication in Transportation Research Part E: Logistics and Transportation Review.
Crowdsourced last-mile delivery is an emerging paradigm in urban logistics, offering a flexible approach to mitigating operational costs and urban congestion. However, its effectiveness depends on the interplay between three key factors: the strategic placement of parcel service points, the task acceptance behavior of occasional couriers, and the operation of a professional fleet alongside them.
This paper addresses these factors simultaneously by developing an integrated simulation-optimization framework that links strategic planning and operational behavior. A key methodological contribution lies in combining a cost-aware facility location model for parcel placement, a behavioral choice model for courier task acceptance, and a vehicle routing solver for the professional fleet.
Using real parcel data and simulated passenger trips from Copenhagen, our results demonstrate that this coordinated framework substantially increases courier participation, reduces professional fleet routing workload, and improves overall system efficiency. The analysis highlights how behavioral modeling and spatial optimization jointly enable cost-effective and scalable collaboration between crowds and fleets in urban delivery networks.
This research was conducted in collaboration with Mina Akbarpour, Stefan Röpke, Soora Rasouli, Otto Anker Nielsen, and Feixiong Liao.