GPU-accelerated Optimization of Fuel Treatments for Mitigating Wildfire Hazard

https://doi.org/10.1016/j.procs.2013.05.262Get rights and content
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Abstract

Fuel treatment is considered a suitable way to mitigate the hazard related to potential wildfires on a landscape. However, designing an optimal spatial layout of treatment units represents a difficult optimization problem. In fact, budget constraints, the probabilistic nature of fire spread and interactions among the different area units composing the whole treatment, give rise to challenging search spaces on typical landscapes. In this paper we formulate such optimization problem with the objective of minimizing the extension of land characterized by high fire hazard. Then, we propose a computational approach that leads to a spatially-optimized treatment layout exploiting Tabu Search and General-Purpose computing on Graphics Processing Units (GPGPU). Using an application example, we also show that the proposed methodology can provide high-quality design solutions in low computing time.

Keywords

Fuel Treatment
GPGPU
Simulation
Optimization
Cellular Automata ;

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Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science.