Fresh food cold chain end distribution path dynamic optimization method based on space-time trajectory clustering
By employing a dynamic path optimization method based on spatiotemporal trajectory clustering and an improved ant colony algorithm, the problem of identifying and optimizing the risks of hidden congestion and product damage in cold chain distribution is solved, thereby improving the intelligence level and robustness of cold chain distribution.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Filing Date
- 2026-06-04
- Publication Date
- 2026-07-17
AI Technical Summary
Existing cold chain delivery route optimization technologies are inadequate in terms of hidden congestion identification, spatiotemporal dynamic perception, deep coupling of loss risk, and adaptive optimization capabilities of algorithms, resulting in low efficiency and poor robustness of fresh food cold chain delivery in complex dynamic environments.
By integrating historical trajectory big data with real-time sensor information, a spatiotemporal density clustering algorithm with time segmentation and adaptive neighborhood is used to identify hidden congestion nodes. A loss assessment model is constructed by combining temperature decay and inventory early warning. An improved ant colony algorithm is used for dynamic path optimization, and a risk perception pheromone update mechanism is embedded to generate a dynamic optimal delivery route.
It significantly improves the accuracy of road network status perception, enables accurate identification of hidden congestion and deep coupling of goods quality monitoring and operational risks, enhances the algorithm's optimization ability and response efficiency in dynamic environments, and optimizes cold chain distribution costs and quality assurance.
Smart Images
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