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An integrated optimization model for fuel management and fire suppression preparedness planning

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  • James Minas
  • John Hearne
  • David Martell

Abstract

Fuel management and suppression preparedness planning are elements of forest fire management that are strongly interrelated with one another. Despite this interrelation, previous forest fire management optimization models have tended to consider these components in isolation from one another. Here we present an integer programming model that incorporates both fuel management and suppression preparedness decisions, thus providing an integrated planning framework. A series of hypothetical test landscapes are used to demonstrate the model’s functionality with easily interpretable results. A number of possible extensions to the model formulation are also discussed. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • James Minas & John Hearne & David Martell, 2015. "An integrated optimization model for fuel management and fire suppression preparedness planning," Annals of Operations Research, Springer, vol. 232(1), pages 201-215, September.
    • Handle: RePEc:spr:annopr:v:232:y:2015:i:1:p:201-215:10.1007/s10479-012-1298-8
    DOI: 10.1007/s10479-012-1298-8
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    References listed on IDEAS

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    1. Dimopoulou, Maria & Giannikos, Ioannis, 2004. "Towards an integrated framework for forest fire control," European Journal of Operational Research, Elsevier, vol. 152(2), pages 476-486, January.
    2. James I. MacLellan & David L. Martell, 1996. "Basing Airtankers for Forest Fire Control in Ontario," Operations Research, INFORMS, vol. 44(5), pages 677-686, October.
    3. Masashi Konoshima & Claire A. Montgomery & Heidi J. Albers & Jeffrey L. Arthur, 2008. "Spatial-Endogenous Fire Risk and Efficient Fuel Management and Timber Harvest," Land Economics, University of Wisconsin Press, vol. 84(3), pages 449-468.
    4. David L. Martell, 2007. "Forest Fire Management," International Series in Operations Research & Management Science, in: Andres Weintraub & Carlos Romero & Trond Bjørndal & Rafael Epstein & Jaime Miranda (ed.), Handbook Of Operations Research In Natural Resources, chapter 0, pages 489-509, Springer.
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    Cited by:

    1. Esther Jose & Puneet Agarwal & Jun Zhuang, 2023. "A data-driven analysis and optimization of the impact of prescribed fire programs on wildfire risk in different regions of the USA," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(1), pages 181-207, August.
    2. Adán Rodríguez-Martínez & Begoña Vitoriano, 2020. "Probability-Based Wildfire Risk Measure for Decision-Making," Mathematics, MDPI, vol. 8(4), pages 1-18, April.
    3. Bashiri, Mahdi & Nikzad, Erfaneh & Eberhard, Andrew & Hearne, John & Oliveira, Fabricio, 2021. "A two stage stochastic programming for asset protection routing and a solution algorithm based on the Progressive Hedging algorithm," Omega, Elsevier, vol. 104(C).
    4. Fu, D.Z. & Zheng, Z.Y. & Shi, H.B. & Xiao, Rui & Huang, G.H. & Li, Y.P., 2017. "A multi-fuel management model for a community-level district heating system under multiple uncertainties," Energy, Elsevier, vol. 128(C), pages 337-356.
    5. Charles Sims & Betsy Heines & Suzanne Lenhart, 2017. "Assessing the Economic Tradeoffs Between Prevention and Suppression of Forest Fires," Working Papers 2017-05, University of Tennessee, Department of Economics.
    6. Yanyan Wang & Mingshu Lyu & Baiqing Sun, 2024. "Emergency resource allocation considering the heterogeneity of affected areas during the COVID-19 pandemic in China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    7. Bhuiyan, Tanveer Hossain & Moseley, Maxwell C. & Medal, Hugh R. & Rashidi, Eghbal & Grala, Robert K., 2019. "A stochastic programming model with endogenous uncertainty for incentivizing fuel reduction treatment under uncertain landowner behavior," European Journal of Operational Research, Elsevier, vol. 277(2), pages 699-718.

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