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Type: Journal Article
Author(s): Dmytro Matsypura; Oleg A. Prokopyev; Aizat Zahar
Publication Date: 2018

Wildfires are a common phenomenon on most continents. They have occurred for an estimated 60 million years and are part of a regular climatic cycle. Nevertheless, wildfires represent a real and continuing problem that can have a major impact on people, wildlife and the environment. The intensity and severity of wildfires can be reduced through fuel management activities. The most common and effective fuel management activity is prescribed burning. We propose a multi-period optimization framework based on mixed integer programming (MIP) techniques to determine the optimal spatial allocation of prescribed burning activities over a finite planning horizon. In contrast to the existing fuel management optimization literature, we model fuel accumulation with Olson’s equation. To capture potential fire spread along with irregular landscape connectivity considerations, we use a graph-theoretical approach that allows us to exploit graph connectivity measures (e.g., the number of connected components) as optimization objectives. The resulting mathematical programs can be tackled by general purpose MIP solvers, while for handling larger instances we propose a simple heuristic. Our computational experiments with test instances constructed based on real-life data reveal interesting insights and demonstrate the advantages and limitations of the proposed approaches.

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Citation: Matsypura, Dmytro; Prokopyev, Oleg A.; Zahar, Aizat. 2018. Wildfire fuel management: network-based models and optimization of prescribed burning. European Journal of Operational Research 264(2):774-796.

Cataloging Information

Topics:
Regions:
Alaska    California    Eastern    Great Basin    Hawaii    Northern Rockies    Northwest    Rocky Mountain    Southern    Southwest    International    National
Keywords:
  • connectivity
  • fire severity
  • fire spread
  • fuel accumulation
  • fuel management
Record Last Modified:
Record Maintained By: FRAMES Staff (https://www.frames.gov/contact)
FRAMES Record Number: 24979