Service-oriented recovery sequencing for flood-exposed underground metro stations: A cascade-gated stochastic multi-criteria framework

Post-flood recovery of underground metro stations requires coordinated restoration of interdependent power, communication, and pedestrian subsystems, yet existing models typically treat physical component repair as equivalent to effective service restoration, obscuring extended periods of zero service capacity behind apparent repair progress. This study develops a service-oriented decision-support framework coupling flood-depth-driven cascading-failure modeling, stochastic Monte Carlo recovery simulation, and a cost–time evaluation with an explicit service-level cascade-gating constraint. Six recovery strategies, spanning cost-prioritizing, time-prioritizing, hierarchy-following, balanced, and two resilience-informed greedy variants (RFVC-Greedy), are evaluated across 100-, 500-, and 1000-year flood scenarios. Three findings hold across scenarios: cost-prioritizing and strict hierarchy-following strategies produce prolonged zero-service intervals; cascade dependencies amplify functionality loss well beyond direct flood damage; and power restoration acts as a force multiplier dominating total resilience variance. The cost–time Pareto knee shifts with severity, with the Balanced strategy forming the knee under the 100-year scenario and the RFVC-Greedy variants under the 500- and 1000-year scenarios; the min cascade vulnerability ( V C ) variant additionally offers the greatest cross-scenario temporal predictability. The framework provides severity-adaptive operational guidance for emergency managers of flood-exposed metro systems and quantifies the structural decoupling between physical repair and service restoration.