Public Transport-Based Crowd-Shipping with Backup Transfers

With the rising urbanization and booming e-commerce, traditional last-mile delivery systems fail to satisfy the need for faster, cheaper, and more environmentally friendly deliveries. Several new approaches are put forward as an alternative to classical delivery systems in this regard, yet none of them offers the same level of flexibility, capacity, reliability, and managerial control by itself. This paper proposes a new last-mile delivery model that combines several new approaches and technologies to address this issue. More precisely, we suggest using public transit as a backbone network completed by automated service points, crowd-shipping, and backup transfers with zero-emission vehicles to provide a low-cost and environmentally friendly express delivery service. The design problem for the envisioned system is formulated as a two-stage stochastic program, and a branch-and-price (BP) algorithm is devised to solve it. Taking advantage of the nearly decomposable structure that would emerge in possible real-world applications, our study presents the first example of using decomposition branching in a BP framework to enhance computational efficiency. Extensive computational studies and simulations with real-world data reveal valuable managerial insights for the proposed system and attest to the efficacy of the suggested methodology.