An optimization framework for healthcare facility fortification: A scenario-based defender–attacker model
Year: 2026
Type: article
Abstract: Healthcare systems are increasingly strained by aging populations, increasing prevalence of chronic diseases, environmental instability, and persistent inequalities in access to care. At the facility level, these pressures are compounded by operational disruptions such as staff shortages, equipment breakdowns, and demand surges, all of which threaten reliable service delivery. Strengthening infrastructure resilience is therefore critical, but comprehensive redesign is rarely feasible under budget constraints. This study proposes an optimization framework for healthcare facility fortification based on a scenario-driven defender-attacker model. The framework guides cost-effective investment decisions that enhance service reliability without requiring prior knowledge of disruption probabilities. Instead, it adopts a worst-case perspective, evaluating resilience through two complementary measures: (i) a vulnerability index obtained by simulating the most damaging disruption under a given defensive configuration, and (ii) an elasticity measure that relates system degradation to the ratio of defensive investment to disruptive effort. By analyzing a range of fortification scenarios, the model identifies non-dominated strategies that balance resilience gains with financial efficiency. The results provide actionable insights for decision-makers and practitioners, supporting targeted reinforcement of healthcare facilities to improve long-term resilience in the face of uncertainty. • Scenario-based defender–attacker model to assess healthcare resilience. • Fortification strategies considering patient preferences with reduced travel distance. • Two resilience metrics: vulnerability index and elasticity measure. • Optimized fortification balances resilience gains with efficient resource use.
Institution: Université de Technologie de Troyes
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,490
Funder: Conseil régional du Grand Est
Award: G2887940939
OpenAlex ID: W7136721254
