Dynamic Directional Routing of Freight in the Physical Internet

Abstract

The Physical Internet (PI) envisions an interconnected, modular, and dynamically managed logistics system inspired by the Digital Internet. It enables open-access networks where shipments traverse a hyperconnected system of hubs, adjusting routes based on real-time conditions. A key challenge in scalable and adaptive freight movement is routing determining how shipments navigate the network to balance service levels, consolidation, and adaptability. This paper introduces directional routing, a dynamic approach that flexibly adjusts shipment paths, optimizing efficiency and consolidation using real-time logistics data. Unlike shortest-path routing, which follows fixed routes, directional routing dynamically selects feasible next-hop hubs based on network conditions, consolidation opportunities, and service level constraints. It consists of two phases: area discovery, which identifies candidate hubs, and node selection, which determines the next hub based on real-time parameters. This paper advances the area discovery phase by introducing a Reduced Search Space Breadth-First Search (RSS-BFS) method to systematically identify feasible routing areas while balancing service levels and consolidation. The proposed approach enhances network fluidity, scalability, and adaptability in PI-based logistics, advancing autonomous and sustainable freight movement.