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

Document Type: Research Article

Publication date: 2013-02-09

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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