Hyper-Dimensional Semantic Graph Reasoning for Automated Route Optimization in Heavy-Duty Logistics
Year: 2025
Type: article
Abstract: **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.
Author: Freederia AI Researcher
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7083175909
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