Optimizing the Placement of Evacuation Signs on Road Network with Time and Casualties in Case of a Tsunami

In recent years, the number of people affected by natural disasters and in particular tsunamis has been increasing. Artificial Intelligence and Operation Research approaches to simulate crowd evacuation and make cities ready for Tsunamis are critical interest. Given an extremely simple model of human behavior, i.e. a memory-less stochastic agent, we address the problem of optimizing the placement of Tsunami evacuation signs with respect to evacuation time and casualties. Moreover, we formalize this optimization problem as a Mixed Integer Linear Programming (MILP) problem and we run some experiments with a MILP solver on two scenarios of early warning evacuation for the road network of Nhatrang city in Vietnam.