Central shelters location planning considering social vulnerability to natural hazards

With the acceleration of urbanization and intensification of climate change, the resilience of smart cities against natural hazards has become crucial. This study proposed a location planning optimization model for central shelters by integrating the social vulnerability assessment of natural hazards with a multi-objective location planning model from a fairness perspective. A social vulnerability assessment index system for regional natural disasters was established through reviewing literature to be combined into the optimization objectives. The new model’s objectives included minimizing the weighted evacuation distance, maximizing vulnerability coverage, and minimizing construction costs. Using Zigong City in Sichuan Province as a case study, the optimization was performed using the NSGA-II algorithm to obtain the Pareto optimal solution set. The TOPSIS method was then employed to identify the final location scheme. The results demonstrated the effectiveness of the new model. This data-driven approach provides actionable insights for spatial planning in smart cities, highlighting the importance of integrating vulnerability metrics with AI-powered optimization for sustainable urban development.