<p>Rainstorm disasters are characterized by sudden onset and severe destructiveness, posing significant threats to the safe operation of urban rail transit systems. Research on the location-allocation problem of emergency facilities in urban rail transit is of great theoretical and practical significance, as it contributes to improve the allocation efficiency of limited emergency resources, to reduce the material inventory costs under rainstorm scenarios, and to promote the development of related optimization models. In this study, a multi-objective material reserve station location–allocation problem model considering demand urgency is established for rainstorm disaster scenarios. Four optimization objectives are considered: the average time satisfaction, the total logistics cost, the degree of unmet demand, and the degree of material allocation disparity. Stations are treated as candidate locations for material reserve stations. In addition, a station priority grading strategy based on demand urgency is proposed to support material reserve planning and emergency resource allocation. A multi-objective hyper-heuristic (MOHH) algorithm is developed to solve the problem, incorporating heuristic operator design in the MRS-LAP problem domain and a CCOD-based operator selection strategy with an Optimal Preservation (OP) solution acceptance criterion in the control domain. Experimental results demonstrate that the proposed algorithm significantly outperforms the comparison algorithms in terms of diversity, convergence, and stability.</p>