Abstract
Wildfires are natural recurrent events, that may be devastating if not addressed correctly. In these situations, where quick and accurate decisions are needed, Operational Research can be helpful for providing fast and robust solutions. This paper focuses on the response actions taken during the suppression stage of a wildfire. A mixed integer linear programming model is proposed to obtain a wildfire suppression strategy, including the wildfire behaviour changes induced by the solution. The selected wildfire suppression strategy is modelled in detail, pointing out which locations to control and their timing, based on available paths between them, avoiding engagement in dangerous situations. A computational study is carried out to determine the most suitable solver to provide exact solutions of the model. Also, a two-stage version of the model is proposed to deal with the multicriteria nature of the problem. A case study is also included to validate the model’s applicability, which is solved using the two proposed versions of the model and an iterative approach to compare their performance.
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Notes
Due to topographic features and wind direction the intensity of the fire varies depending on the arrival direction.
This value has been adopted according to Coffin and Saltzman (2000), who state that for comparing the running times, samples in the range of 30-40 observations per treatment group should be sufficient.
https://landfire.gov/lcp.php accessed December 2022.
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Acknowledgements
We acknowledge the authors of FlamMap and the Landfire program for having free available tools and data.
Funding
Bibiana Granda and Begoña Vitoriano have been supported by the Research National Agency of Spain grant number PID2019-108679RBI00/ AEI/10.13039/501100011033. José Rui Figueira has been supported by Portuguese national funds through the FCT - Foundation for Science and Technology, I.P., grant number UIDB/00097/2020.
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Granda, B., Vitoriano, B. & Figueira, J.R. A mathematical programming approach for a wildfire suppression problem. Oper Res Int J 25, 16 (2025). https://doi.org/10.1007/s12351-024-00882-1
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DOI: https://doi.org/10.1007/s12351-024-00882-1