In disaster scenarios,the application of UAV(Unmanned Aerial Vehicle)for resource delivery holds con-siderable promise.However,the complexity and volatility of emergency environments,along with the spatial and temporal uncertainties associated with various unexpected events,can lead to inaccuracies in assessing resource demands at target points,which in turn may affect the UAV task allocation strategies in resource distribution.To address this issue,a two-stage robust optimization approach is introduced into the UAV task assignmet model.By integrating UAV assignment with task allocation,the model leverages the resources of the UAV fleet to minimize task assignment costs under maximum de-mand variability.This paper models the relationship between injury severity levels and resource demand variations,catego-rizing resource demand into three levels to achieve an accurate representation of total task allocation cost variations.The C&CG(Column-and-Constraint Generation)algorithm is used to address UAV task assignment under uncertain resource de-mand conditions.Finally,three types of experiments were designed and the simulation results validated the effectiveness and superiority of the algorithm.Compared to the deterministic model,this algorithm showed greater robustness in handling demand variation.
维普
万方数据