  Disaster management is a complex problem demanding sophisticated modeling
approaches. We propose utilizing a hybrid method involving inverse optimization
to parameterize the cost functions for a road network's traffic equilibrium
problem and employing a modified version of Fan and Liu (2010)'s two-stage
stochastic model to make protection decisions using the information gained from
inverse optimization. We demonstrate the framework using two types of cost
functions for the traffic equilibrium problem and show that accurate
parameterizations of cost functions can change spending on protection decisions
in most of our experiments.
