Community logistics and dynamic community partitioning: A new approach for solving e-commerce last mile delivery

Last mile delivery shows an increasingly tough challenge for logistics service providers due to the rapidly expanding e-commerce sales around the globe. To ease the implementation of last mile delivery, an effec-tive delivery strategy is to predetermine the service regions of vehicles before optimizing their delivery routes. On this ground, this paper proposes a new delivery strategy named Community Logistics (CL) to generate vehicle service region and departure time dynamically. Through adopting this new delivery strategy, we transform the original last mile delivery to a new type of research problem, namely dy-namic community partitioning problem (DCPP), with an aim to strike a balance between vehicle service region range, order delay time and vehicle capacity usage based on the real-time order arrivals and ve-hicle availability status. We present a Markov decision process (MDP) model for the DCPP and develop a heuristic solution approach to solve this MDP model. Numerical results demonstrate significant benefits of the proposed solution framework and delivery strategy.(c) 2022 Elsevier B.V. All rights reserved.