Green urban logistics path planning design based on physical network system in the context of artificial intelligence

To address the issue of unreasonable route planning in modern logistics intelligent distribution, a comprehensive, efficient, and practical path planning method is provided by modern logistics intelligent distribution. This study takes a comprehensive multimodal transportation perspective between cities as its starting point. Firstly, a physical network system model describes logistics distribution's fundamental physical network elements. Additionally, a logistics service network system model is established to depict the service network elements of logistics distribution. These two models are then combined. Building upon this foundation, variables such as risk and cost in logistics path planning are examined and considered, leading to the design of a logistics path planning model. Simulation analysis is employed in this study for data analysis. Analyzing section utilization and planning results reveals key information in logistics path planning. Segment 4 exhibits the lowest utilization rate at 46.2%, while Segment 7 demonstrates the highest utilization rate at 100%. This indicates that the model favors segment 7 as the primary path due to its superior physical facility elements and road conditions. By integrating section planning with cost and risk considerations, the optimal planning path is determined to be 1-3-6-7, encompassing sections 2, 7, and 10. This plan is based on the analysis results of the model and is considered the most economical and safe logistics path after comprehensive deliberation. The designed green logistics path planning model for the physical network system enables comprehensive planning of combined logistics routes, thereby enhancing the distribution path. The studied and designed green logistics path planning model of the physical network system allows for a comprehensive perspective in planning combined logistics traffic paths, resulting in improved distribution paths. This presents a novel and effective path-planning method for modern logistics intelligent distribution, accomplishing the research objectives and providing important references for subsequent related research.