A Simulation and Stochastic Integer Programming Approach to Wildfire Initial Attack Planning

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Wildfires are a threat to public safety, property, and forests. Wildfire managers deploy fighting resources to fire bases before fires occur and dispatch them to fires during the initial attack to minimize the number of escaped fires that can cause unacceptable costs and losses. To address the deployment and dispatch problem, we combine fire behavior simulation and a two-stage stochastic integer programming model called the explicit fire growth response model (EFGRM) to make deployment decisions in the first stage before fires occur and make dispatch decisions regarding the optimal mix of resources to send to multiple fires in each fire day scenario in the second stage after fires occur. The objective is to minimize the number of escaped fires, cost of resource deployment, expected suppression cost, and net value change. We use our methodology to position dozers in Texas District 12 (TX12), a fire planning unit in East Texas managed by the Texas Forest Service (TFS). The results reveal that the initial distribution of dozers in TX12 at the time of this study was not consistent with the historical density of fires. The results of our methodology suggest a different distribution of dozers across TX12.

Keywords: fire simulation; fire suppression; optimization; stochastic programming; wildfire management

Document Type: Research Article

DOI: http://dx.doi.org/10.5849/forsci.11-022

Publication date: February 23, 2013

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