As the global population ages rapidly, ensuring the accessibility of senior centers is crucial for supporting the well-being and quality of life of older adults. This study aims to address the facility location problem for senior centers in upcoming super-aging societies. An optimization model is developed using a genetic algorithm to determine the optimal locations of senior centers. The objective is to minimize travel distances for older adults while accounting for constraints such as mobility limitations and the existing distribution of senior centers. The elbow method is employed to identify the optimal number of new centers, balancing service accessibility and resource allocation. Open data sources, i.e., floating population and geographic information in Seoul, are used to estimate demand at various locations. The results show that adding up to 15 new centers in Seoul effectively reduced average travel distances for older adults by 24%, from 0.85 km to 0.64 km. The introduction of these new centers is prioritized based on their impact on the community, i.e., reducing travel distances and redistributing demand from overburdened facilities. These findings provide a data-driven framework for urban planners and policymakers to strategically enhance senior service networks in rapidly aging societies. By improving access to senior centers, this approach can help promote active aging, reduce social isolation, and ensure a better quality of life for older adults.