【摘要】 为应对气象灾害的应急响应和资源调度挑战，研究提出一种面向气象灾害应急的多阶段智能调度与资源分配算法。方法上，结合自适应参数的改进差分进化算法与时空网络流模型，用于阶段智能调度；提出基于非支配排序遗传算法Ⅱ与蚁群优化相结合的资源分配与救援队伍调配模型。实验结果表明，在灾中调度中，所提算法的响应时间随灾点规模增加，从76.5分钟上升至82.3分钟；在资源分配与队伍调配中，研究所提算法运行时间低于10秒，救援响应时间由55分钟下降至25分钟，且任务完成率在主城与沿江带接近98%。研究表明，该多阶段智能调度与分配方法有效提升了气象灾害应急的响应效率与公平性，为智能化灾害应急管理提供了重要技术支撑。更多还原

【Abstract】 To address the challenges of emergency response and resource allocation in meteorological disasters, a multi-stage intelligent scheduling and resource allocation algorithm for meteorological disaster emergency response is proposed. Methodologically, an improved differential evolution algorithm combined with adaptive parameters and a spatiotemporal network flow model are used for stage intelligent scheduling; And propose a resource allocation and rescue team deployment model based on the combination of non dominated sorting genetic algorithm II and ant colony optimization. Experimental results show that in disaster scheduling, the response time of the proposed algorithm increases from 76.5 minutes to 82.3 minutes as the scale of disaster points increases; In resource allocation and team deployment, the algorithm proposed by the research institute has a running time of less than 10 seconds, the rescue response time has decreased from 55 minutes to 25 minutes, and the task completion rate is close to 98% in the main city and along the Yangtze River. Research has shown that this multi-stage intelligent scheduling and allocation method effectively improves the response efficiency and fairness of meteorological disaster emergency, providing important technical support for intelligent disaster emergency management.更多还原