Optimizing Sign Placements for Crowd Evacuation on Road Network in Case of Tsunami Alert

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 prepare cities for Tsunamis are of 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 formalise this optimisation problem as a Mixed Integer Linear Programming (MILP) problem and we ran some experiments with a MILP solver to give an early warning for the evacuation of the road network of Nhatrang city in Vietnam.