Optimizing Urban Logistics: Vehicle Routing Problem With Underground Transportation

In response to increasing congestion and inefficiencies in urban freight transportation systems, driven by the rapid rise of e-commerce and urbanization, underground logistics are emerging as a promising alternative. This study introduces the Vehicle Routing Problem with Underground Transportation (VRP-UT), a novel model that integrates traditional vehicle routing with underground logistics facilities to optimize urban deliveries. To address the model’s complexity, we propose a hybrid solution approach that combines Q-learning with pruning techniques, enhancing route optimization and minimizing unnecessary operations. Comprehensive numerical and sensitivity analyses further validate the model’s effectiveness, positioning VRP-UT as a scalable and efficient solution to meet growing urban logistics demands while supporting sustainable development. A case study, including sensitivity analysis based on Seoul Subway Line 3, demonstrates the practical applicability of the VRP-UT model, highlighting its potential to alleviate surface-level traffic congestion, reduce operational costs, and shorten delivery times in densely populated urban areas.