Stochastic last-mile delivery with crowdshipping

Abstract For the predicted growth of e-commerce, supply chains need to adapt to new conditions, so that delivery can be fast, cheap and reliable. The key to success is the last-mile product delivery (LMD) – the last stage of the supply chain, where the ordered product is delivered to the final consumer’s location. One innovative proposal puts foundations in a new delivery model where a professional delivery fleet (PF) is supplemented partially or fully with crowdshipping. The main idea of crowdshipping is to involve ordinary people – in our case in-store shoppers – in the delivery of packages to other customers. In return, occasional couriers (OC) are offered a small compensation. In hitherto formulated problems it was assumed that OCs always accept delivery tasks assigned to them. In this paper we consider OCs as independent agents, which are free to reject assignments. The main contribution of the paper is an original bi-level methodology for matching and routing problem in LMD with OCs and the PF. The goal is to use crowdshipping to reduce the total delivery cost in a same-day last-mile delivery system with respect to occasional couriers’ freedom to accept or reject the assigned delivery. We introduce probability to represent each OC’s willingness to perform the delivery to a given final customer. We study the OCs’ willingness to accept or reject delivery tasks assigned to them and the influence of their decision on the total delivery cost associated to both the OCs’ compensation fees and the delivery cost generated by the PF used for the delivery of remaining parcels.