A Simulation-Based Optimization Approach to the Firefighting Resource Scheduling Problem

In recent years, the number of forest fires has increased significantly. The main factors behind these disasters are rising temperatures and population growth. Optimization and simulation have been widely applied to forest firefighting problems, making it possible to improve the effectiveness and speed of firefighting actions. This work presents a forest firefighting resource scheduling problem, where a single firefighting resource is fighting 10 ignitions. A Genetic Algorithm (GA) is used to find the near-optimal sequence of actions, taking into account the maximization of the total unburned area. The solution found by the GA is evaluated using a Discrete-Event Simulation model developed in FlexSim software, thus validating the solution. Then, a simulation-based optimization approach is developed, involving uncertainty in some parameters.