• We introduce a strategic Defender-Attacker-Defender model for relief train deployment and infrastructure protection. • Our approach incorporates scenario-dependent disruptions at the attacker-stage to enhance robustness in disaster response planning. • We develop a progressive hedging-inspired algorithm to tackle the problem’s computational challenges. • Our results show that accounting for uncertainty and interactions can improve overall survival probability by up to 70%.
Hager et al. (Tue,) studied this question.
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