Optimizing Urban Logistics: Vehicle Routing Problem With Underground Transportation
Ho Young Jeong, Byung Duk Song
Abstract
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.