  Resilient operation of interdependent infrastructures against compound hazard
events is essential for maintaining societal well-being. To address consequence
assessment challenges in this problem space, we propose a novel tri-level
optimization model applied to a proof-of-concept case study with fuel
distribution and transportation networks -- encompassing one realistic network;
one fictitious, yet realistic network; as well as networks drawn from three
synthetic distributions. 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) to
minimize unmet demand at gas stations. A notional attacker aims to
hypothetically disrupt normal operations by reducing supply at the supply
terminals, and the notional defender aims to identify best proxy defense policy
options which include hardening supply terminals or allowing alternative
distribution methods such as trucking reserve supplies. We solve our DAD
formulation at a metropolitan scale and present practical defense policy
insights against hypothetical compound hazards. We demonstrate the
generalizability of our framework by presenting results for a realistic
network; a fictitious, yet realistic network; as well as for three networks
drawn from synthetic distributions. Additionally, we demonstrate the
scalability of the framework by investigating runtime performance as a function
of the network size. Steps for future research are also discussed.
