A Dynamic Framework for Community-Facility Siting with Inter-Community Competition

Locating community facilities is a long-term, daunting task for governments, requiring ongoing budget or policy updates for gradual improvement. This study proposes a bi-objective multi-scenario dynamic model (BOMSDM) for community-facility siting, which aims to maximize service efficiency and social equity while considering variable facility numbers and inter-community competition. This study also provides a framework to demonstrate how the newly proposed model operates. This framework includes the BOMSDM itself, the data collection and processing method, and the constrained NSGA-II as the computational algorithm. Under this framework, the BOMSDM, along with three comparative frameworks derived from traditional models-including a random allocation non-incremental model, a random allocation incremental model, and an average allocation non-incremental model-was applied to a real-world scenario in Shaoxing. The results demonstrate the effectiveness and superiority of BOMSDM: it significantly outperforms the realistic solution in terms of service efficiency, fairness, and community allocation rate. Compared to alternative frameworks, BOMSDM sacrifices some objective values in scenarios without facility redundancy to ensure higher community coverage while exhibiting rapid improvement in objective values when redundancy is present, highlighting the framework's flexibility. This framework provides government decision-makers with an effective tool for community-facility site selection.