Crowdshipping problem with dynamic compensations and transshipments

Rapid urban growth and consequent increase in e-commerce demand make urban logistics a harder task than ever. The growing size of urban delivery operations not only entails operational challenges but also generates several negative externalities, such as increased traffic, pollution, noise, and accidents. This trend creates a pressing need for efficient delivery mechanisms that are more economical and environmentally friendly than existing systems. Crowdshipping, wherein ordinary members of the society partake in delivery operations for a small compensation, is one of the answers that cater to this need and has attracted considerable research interest recently. However, designing compensation mechanisms to prompt efficient participation from the public remains largely unexplored in the literature. In this study, we devise a dynamic compensation scheme for crowdshipping operations in a many-to-many express delivery framework, where the crowdshipper compensations are determined based on spatial and temporal distributions of the delivery demand and continually updated during the service time to leverage the crowd participation as needed. To address the resulting complex network management problem, we derive analytical solutions for compensation optimization and use these results along with effective pruning strategies to build a lookup table to simultaneously determine package routes and compensation offers in real time. Computational studies and extensive simulations conducted with real-world data show that our proposed approach can provide significant cost savings and considerably reduce operational costs and other transport-related negative externalities when compared to classical delivery modes, crowdshipping with static compensations, and crowdshipping without transshipment.