An optimization-based approach for an integrated forest fire monitoring system with multiple technologies and surveillance drones

Wildfires pose a significant threat to forests and the delicate natural balance. In this work, we present a novel optimization approach for designing forest fire monitoring systems that incorporate surveillance towers, monitoring balloons, and drone technology, which have gained popularity in recent years for monitoring, logistics, and civil applications. We develop a compact mixed-integer linear programming model that includes location decisions for multiple monitoring technologies and routing of drones among monitoring facilities to achieve the most extensive possible terrain coverage. Additionally, we propose a matheuristic algorithm that comprises six components: a solution procedure, perturbation procedures, local search procedures, a call to the general-purpose solver to solve a mixed-integer linear programming model, a global reset strategy, a local reset strategy, and an acceptance criterion. We test the proposed model and algorithm on a set of random instances and a real-life case study in Chile. While the proposed model can only solve small instances, the matheuristic can find good-quality solutions for all instances. This study can aid the government and private sector in designing an integrated fire monitoring system that leverages watchtowers, monitoring balloons, and drones.