Abstract
Wildfires increasingly threaten the operation and stability of regional socio-economic systems, where infrastructure, population, and environmental conditions are tightly interconnected. To enhance operational efficiency and strengthen community resilience, this study develops an integrated optimization framework for wildfire evacuation system design based on mixed-integer programming. The model simultaneously determines the locations of primary and secondary shelters and establishes both main and backup evacuation linkages, forming a dual-stage structure that ensures continuous accessibility even under disrupted conditions such as road blockages or fire spread. Wildfire risk indices derived from topographic and environmental data are incorporated to support risk-aware and balanced shelter allocation. A case study of Uiryeong County, South Korea, demonstrates that the proposed framework effectively improves evacuation efficiency and system reliability, producing spatially coherent and adaptive evacuation plans under diverse disruption scenarios. The findings highlight how operation optimization can enhance socio-economic system resilience and sustainability when facing large-scale environmental disruptions.