Forest fires are a growing environmental, social and economic threat, especially in regions with high vegetation density and frequent ignition occurrences. This thesis addresses the problem of optimizing the allocation of firefighting resources to minimize the impact of forest fires, focusing on scenarios with multiple simultaneous ignitions and limited resources. The research proposes and evaluates several approaches, including single-objective, lexicographic, and multi-objective optimization formulations, to support strategic decision-making in fire suppression. First, a constructive heuristic is developed to quickly generate feasible initial solutions to the firefighting resource allocation and routing problem. Then, metaheuristics, such as the genetic algorithm and differential evolution algorithm are implemented to explore complex and large-scale solution spaces effectively. The proposed methods are validated using a case-study from the Braga district, Portugal, a region characterized by recurrent and severe forest fires. Several operational scenarios are studied, considering different levels of resource availability. The models aim to minimize the number of fires extinguished after 90 minutes, the total burned area, the time required to extinguish all fires, the total used water and the number of firefighting resources needed to extinguish all fires. The results show that metaheuristic-based approaches are efficient in terms of solution quality and adaptability under resource-limited conditions. In particular, the multi-objective solutions allows the decision-maker to identify the compromise solutions and choose according to his/her preferences. This thesis contributes to the development of advanced optimization models for forest fire suppression and presents a computational implementation that can serve as a decision support tool for civil protection entities. The findings highlight the importance of integrating smart resource allocation strategies into operational response plans to increase resilience and reduce the impacts of forest fires, especially in the face of increasing challenges posed by climate change.

Forest fires are natural phenomena that have become increasingly serious in recent decades. It has therefore become essential to manage firefighting in order to prevent and reduce the damage caused by fires, such as loss of life, the impact on the economy, and damage to ecosystems. In order to reduce the impact of a fire, firefighting resources must be available and deployed to extinguish a given ignition in order to be as effective as possible in fighting fires. In this work, we address the problem of dispatching and routing a set of resources to attack multiple fires. Given the need for quick decisions, we propose a constructive heuristic. The approach is based on a time discretization and on estimates of the growth of the different fires. The heuristic has the advantage of producing results in a short time, indicating where and when each resource should move to extinguish the fire, so that the burned area is as small as possible. A set of 60 instances, comprising 5, 7, and 10 resources to extinguish 20 and 30 ignitions, is generated to test and validate four variants of the constructive heuristic. A case study in northern Portugal is presented to demonstrate the practical feasibility of the proposed approach. The results showed the effectiveness of the constructive heuristic, which may be used to support firefighting services in making decisions.