Skip to Main Content
U.S. Forest Service
Caring for the land and serving people

United States Department of Agriculture

Home > Search > Publication Information

  1. Share via EmailShare on FacebookShare on LinkedInShare on Twitter
    Dislike this pubLike this pub
    Author(s): Alex Taylor Masarie
    Date: 2011
    Source: Fort Collins, CO: Colorado State University. Thesis. 80 p.
    Publication Series: Miscellaneous Publication
    PDF: View PDF  (1.87 MB)


    Resource allocation for wildland fire suppression problems, referred to here as Fire-S problems, have been studied for over a century. Not only have the many variants of the base Fire-S problem made it such a durable one to study, but advances in suppression technology and our ever-expanding knowledge of and experience with wildland fire behavior have required almost constant reformulations that introduce new techniques. Lately, there has been a strong push towards randomized or stochastic treatments because of their appeal to fire managers as planning tools. A multistage stochastic program with variable recourse is proposed and explored in this paper as an answer to a single-fire planning version of the Fire-S problem. The Fire-S stochastic program is discretized for implementation according to scenario trees, which this paper supports as a highly useful tool in the stochastic context. Our Fire-S model has a high level of complexity and is parameterized with a complicated hierarchical cluster analysis of historical weather data. The cluster analysis has some incredibly interesting features and stands alone as an interesting technique apart from its application as a parameterization tool in this paper. We critique the planning model in terms of its complexity and options for an operational version are discussed. Although we assume no interaction between fire spread and suppression resources, the possibility of incorporating such an interaction to move towards an operational, stochastic model is outlined. A suppression budget analysis is performed and the familiar "production function" fire suppression curve is created, which strongly indicates the Fire-S model performs in accordance with fire economic theory as well as its deterministic counterparts. Overall, this exploratory study demonstrates a promising future for the existence of tractable stochastic solutions to all variants of Fire-S problems.

    Publication Notes

    • You may send email to to request a hard copy of this publication.
    • (Please specify exactly which publication you are requesting and your mailing address.)
    • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
    • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.


    Masarie, Alex Taylor. 2011. Resource allocation for wildland fire suppression planning using a stochastic program. Fort Collins, CO: Colorado State University. Thesis. 80 p.


    wildland fire suppression, resource allocation, Fire-S stochastic program

    Related Search

    XML: View XML
Show More
Show Fewer
Jump to Top of Page