healthcare service delivery.Background: Artificial intelligence (AI) in urban and multimodal transport has demonstrated strong …-ready architecture that links data fusion, multi-objective optimization, and electrification constraints into daily multimodal …-agnostic, supporting evolutionary and learning-based techniques. Conclusions: A Thessaloniki-based multimodal case study demonstrates how …

bioenergy and bioproduct production. This study analyzes how combining artificial intelligence (AI) with multimodal transport … multimodal transport), the intelligence domain (AI-based decision making), and the strategic approach. Results: The outcomes … accuracy for transport costs. Conclusions: The integration of AI and multimodal networks builds resilient and sustainable …

Background: The transportation of petroleum products via multimodal logistics systems is a complex process subject to … increasingly depends on multimodal logistics systems, where operational risks and process inefficiencies can significantly impact …. The workflow simulation replicated real-world multimodal oil operations across maritime, rail, road, and inland waterway …

Corridor. However, multimodal freight transport remains under-optimized due to infrastructure bottlenecks, uneven cargo flows …-based simulation model for analyzing multimodal transportation in Kazakhstan. The model integrates railway, road, and maritime … uncertainty and can support decision-making in transport planning. The novelty lies in the integrated simulation of multimodal …

We examine the economic and environmental impacts of improvements and disruptions in multimodal transport networks. Our …