一种求解无人机与车辆协同路径问题的迭代贪婪搜索方法
By employing an iterative greedy search method combined with guided destructive recombination and rapid similarity detection, the paths for UAVs and vehicles are optimized, solving the challenge of efficiently solving the VRPD problem and achieving highly robust and high-quality path optimization.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHANGHAI JIAOTONG UNIV
- Filing Date
- 2025-06-24
- Publication Date
- 2026-07-17
AI Technical Summary
Existing methods for solving the unmanned vehicle cooperative path problem (VRPD) are difficult to solve efficiently, especially due to the complexity of vehicle and unmanned vehicle movement synchronization and task synchronization. Furthermore, existing methods struggle to achieve highly robust and high-quality solutions.
An iterative greedy search method is adopted, which optimizes vehicle and drone paths by initializing the population, guided destruction and recombination operations, fast similarity detection and two-layer hybrid neighborhood search, combined with efficient UAV path construction operations, to achieve efficient solution.
It improves the robustness and quality of solving VRPD problems, reduces redundant calculations, and enhances solution efficiency and accuracy.
Smart Images
Figure CN120593768B_ABST