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The wildfire suppression problem with multiple types of resources

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  • Avci, Mualla Gonca
  • Avci, Mustafa
  • Battarra, Maria
  • Erdoğan, Güneş

Abstract

The frequency and impact of wildfires have considerably increased in the past decade, due to the extreme weather conditions as well as the increased population density. The aim of this study is to introduce, model, and solve a wildfire suppression problem that involves multiple types of fire suppression resources and their operational characteristics. Two integer programming (IP) formulations, a basic IP and its reformulation with combinatorial Benders’ cuts, are presented. The performances of the proposed formulations are evaluated on a set of randomly generated instances. The results indicate that the proposed formulations are able to obtain high quality upper and lower bounds. Extensive numerical experiments are performed to analyse the effects of several operational constraints on the computational performance of the models. A case study arising in Yatağan district of Muğla province of Türkiye is presented.

Suggested Citation

  • Avci, Mualla Gonca & Avci, Mustafa & Battarra, Maria & Erdoğan, Güneş, 2024. "The wildfire suppression problem with multiple types of resources," European Journal of Operational Research, Elsevier, vol. 316(2), pages 488-502.
    • Handle: RePEc:eee:ejores:v:316:y:2024:i:2:p:488-502
    DOI: 10.1016/j.ejor.2024.03.005
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    References listed on IDEAS

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    1. Eghbal Rashidi & Hugh Medal & Aaron Hoskins, 2018. "An attacker‐defender model for analyzing the vulnerability of initial attack in wildfire suppression," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(2), pages 120-134, March.
    2. Smith, J. Cole & Song, Yongjia, 2020. "A survey of network interdiction models and algorithms," European Journal of Operational Research, Elsevier, vol. 283(3), pages 797-811.
    3. Mendes, André Bergsten & e Alvelos, Filipe Pereira, 2023. "Iterated local search for the placement of wildland fire suppression resources," European Journal of Operational Research, Elsevier, vol. 304(3), pages 887-900.
    4. Boysen, Nils & Emde, Simon & Schwerdfeger, Stefan, 2022. "Crowdshipping by employees of distribution centers: Optimization approaches for matching supply and demand," European Journal of Operational Research, Elsevier, vol. 296(2), pages 539-556.
    5. Gianni Codato & Matteo Fischetti, 2006. "Combinatorial Benders' Cuts for Mixed-Integer Linear Programming," Operations Research, INFORMS, vol. 54(4), pages 756-766, August.
    6. Wang, Yun & Zou, Runmin & Liu, Fang & Zhang, Lingjun & Liu, Qianyi, 2021. "A review of wind speed and wind power forecasting with deep neural networks," Applied Energy, Elsevier, vol. 304(C).
    7. Rashidi, Eghbal & Medal, Hugh & Gordon, Jason & Grala, Robert & Varner, Morgan, 2017. "A maximal covering location-based model for analyzing the vulnerability of landscapes to wildfires: Assessing the worst-case scenario," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1095-1105.
    8. Erdoğan, Güneş & Battarra, Maria & Wolfler Calvo, Roberto, 2015. "An exact algorithm for the static rebalancing problem arising in bicycle sharing systems," European Journal of Operational Research, Elsevier, vol. 245(3), pages 667-679.
    9. Demir, Murat, 2007. "Impacts, management and functional planning criterion of forest road network system in Turkey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(1), pages 56-68, January.
    10. 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.
    11. O. Zambon, Mauricio J. & J. de Rezende, Pedro & C. de Souza, Cid, 2019. "Solving the geometric firefighter routing problem via integer programming," European Journal of Operational Research, Elsevier, vol. 274(3), pages 1090-1101.
    12. Matsypura, Dmytro & Prokopyev, Oleg A. & Zahar, Aizat, 2018. "Wildfire fuel management: Network-based models and optimization of prescribed burning," European Journal of Operational Research, Elsevier, vol. 264(2), pages 774-796.
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