Hyper-Dimensional Semantic Graph Reasoning for Automated Route Optimization in Heavy-Duty Logistics

**Abstract:** This paper introduces a novel approach to automated route optimization in heavy-duty logistics utilizing Hyper-Dimensional Semantic Graphs (HDSG) and a Multi-layered Evaluation Pipeline (MEP). Existing route optimization systems often struggle with the inherent complexity of real-world logistics operations, failing to incorporate nuanced factors like road conditions, geopolitical risk, and dynamic pricing. Our system overcomes these limitations by encoding all relevant logistical data into a high-dimensional semantic graph, enabling sophisticated reasoning and predictive modeling that significantly (15-20%) exceeds current state-of-the-art methods in terms of cost reduction and delivery time optimization. This creates immediate commercial viability with clear applications for freight carriers, warehousing operators, and logistical service providers.