A General Model for Wildfire Suppression Problems

Wildfires are an important problem of our time, causing substantial economic, ecological, and infrastructural damage. The operations research community has long been involved in developing decision support models for fire suppression, and modeling approaches vary greatly. An important class of models is based on encoding a landscape using a graph and integrating fire propagation and suppression strategies within the optimization process. Several works in the literature describe graph-based models, which differ in the assumptions about fire propagation, the objective function, and the features considered. In this work, we propose a new mixed-integer programming (MIP) model that includes various features from previous research. In experiments, we compare this model against a more specialized model using benchmark instances from the literature. The results indicate that the proposed model is easier to solve and performs competitively against more sophisticated algorithms.