A Tri-Level Optimization Model for Interdependent Infrastructure Network Resilience Against Compound Hazard Events

To address consequence assessment challenges associated with resilient operation of interdependent infrastructures against compound hazard events, we propose a novel policy-guided tri-level optimization model applied to a proof-of-concept case study with fuel distribution and transportation networks. Mathematically, our approach takes the form of a defender-attacker-defender (DAD) model-a multi-agent tri-level optimization, comprised of a defender, attacker, and an operator acting in sequence. Here, our notional operator may choose proxy actions to operate an interdependent system comprised of fuel terminals and gas stations (functioning as supplies) and a transportation network with traffic flow (functioning as demand) so as to minimize unmet demand at gas stations. A notional attacker aims to hypothetically disrupt normal operations by reducing supply at the supply terminals and close roadways to further congestion, and the notional defender aims to identify best proxy defense policy options which includes hardening supply terminals or allowing alternative distribution methods such as trucking reserve supplies. We also propose to investigate solving our DAD formulation at a reasonable (metropolitan area) scale with an adaptation of active constraint learning. Solving such a model, especially at a real-world scale, would aid in exploring the trade-offs between the cost of implementing a defense policy and the effect it has on system impacts.