Jan 2026· arXiv.org· Vol abs/2603.29865· 0 citations· 30 references
Computer Science
Abstract
Wildfires cause major losses worldwide, and the frequency of fire-weather conditions is likely to increase in many regions. We study the allocation of suppression resources over time on a graph-based representation of a landscape to slow down fire propagation. Our contributions are theoretical and methodological. First, we prove strong NP-completeness on planar graphs for this problem and two related variants, and on full weighted directed grids for two of the three problems. We also show that this problem remains strongly NP-complete when all resources are released simultaneously. Second, we propose a new mixed-integer programming (MIP) formulation that obtains state-of-the-art results, showing that MIP is a competitive approach contrary to earlier findings. Third, showing that existing benchmarks lack realism and difficulty, we introduce a physics-grounded instance generator based on Rothermel's surface fire spread model. We use these diverse instances to benchmark the literature, identifying the specific conditions where each algorithm succeeds or fails.
Wildfires are an increasing threat in Central Europe and pose challenges for protective forests and areas at the wildland–urban interface (WUI). Understanding, describing and predicting fire behaviour is therefore becoming more relevant for fire management. This work aims to reconstruct the fire spread behaviour of pas...
K. Kuhnen, M. S. Andrade, Mortimer M. Müller et al.· Fire· 1 citation
This article analyzes the parallel scalability of the WILDFIRES-IGA-ADS simulator on a concurrent server with shared memory and employs the isogeometric finite element method with tensor product B-spline basis functions, explicit time integration schemes, and a linear computational cost solver resulting from the Kronec...
Juliusz Wasieleski, A. Medina, Maciej Woźniak et al.· International Conference on...· 0 citations
Abstract. Wildfire activity in Canada has increased significantly in recent decades, shifting to larger, more frequent fires and the emergence of megafires (>10,000 ha) across various ecozones. These events typically exhibit complex spatial patterns of burn severity, including larger and more homogeneous patches of hig...
E.J. Krieger-Pottruff, Sophie L. Wilkinson· The International Archives o...· 0 citations
Recently, a stochastic forest fire model was proposed in which the forest state is represented by sub-probability densities of firing, green, and burnt trees, whose evolution is governed by a master equation formulated as a system of integro-differential equations. Within this framework, the present paper restricts att...
R. Beneduci, Giovanni Mascali· Zeitschrift für Angewandte M...· 0 citations
A physically interpretable, data-driven framework was developed to elucidate causal interactions, model, and predict wildfire-induced building damage across California. More than 100,000 damage inspection records (2013 to 2024) were used to model building damage from static environmental variables (topography, vegetati...
S. Bar, Shu Li, T. Banerjee· Science Advances· 0 citations
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
