Emergency reserve storage location is one of the crucial parts of the emergency rescue system and is a long-term strategic decision-making issue. Continued impact of disasters can lead to disruptions in emergency reserve storages that make it difficult to provide emergency support in a timely manner. Demand points where rescue services cannot be accessed quickly require rescue services from more distant reserves. In this paper, the fuzzy fault tree (FFT) was employed to determine the outage probability of the reserve storage quantitatively. With the aim of minimizing the overall cost of emergency response while maximizing demand coverage, an emergency reserve storage location model was devised for interruption scenarios. To solve this model, the multiple population genetic algorithm (MPGA) relying on elite strategy was utilized. The research results show that, compared with the traditional emergency reserve storage location optimization model, the emergency storage location optimization model under the interruption scenario can effectively reduce the penalty cost generated by the impact of the disruption, and with the increase of the location size, the proportion of the penalty cost reduction gradually increases. Decision makers can weigh costs and coverage levels based on different risk preferences to determine the optimal location option.