A Robust Approach for the Prepositioning of Resources for Wildfire Suppression

Francisco Marques (), Agostinho Agra (), Helena Alvelos (), Ana Raquel Xambre () and Filipe Alvelos ()
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Francisco Marques: University of Aveiro
Agostinho Agra: Universidade de Lisboa, Departamento de Ciências Matemáticas and Centro de Estudos Matemáticos (CEMS.UL), Faculdade de Ciências
Helena Alvelos: University of Aveiro, Department of Economics, Management, Industrial Engineering and Tourism/Center for Research and Development in Mathematics and Applications
Ana Raquel Xambre: University of Aveiro, Department of Economics, Management, Industrial Engineering and Tourism/Center for Research and Development in Mathematics and Applications
Filipe Alvelos: University of Minho, Department of Production and Systems/ALGORITMI Research Center/LASI, School of Engineering

A chapter in Advances in Optimization and Wildfire, 2026, pp 155-168 from Springer

Abstract: Abstract We consider the problem of prepositioning a set of firefighting resources for wildfire suppression. As wildfires are highly affected by uncertainty we devise a two-stage model where the prepositioning of resources are first-stage decisions and the movement of these resources after the fire ignitions are known are the second-stage decisions. We use the minimum travel time principle and mixed integer programming to model the fire spread in the landscape and decisions related to the prepositioning of resources and their movement to attack positions. To model uncertainty we use robust optimization based on a discrete set of scenarios which represent ignition locations, wind speed and directions. As the size of the model grows considerably with the number of scenarios, a row-and-column decomposition algorithm is proposed. Computational experiments based on an actual landscape are reported showing the efficiency of the decomposition algorithm.

Keywords: Wildfire suppression; Prepositioning of resources; Robust optimization; Decomposition algorithm (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-03108-2_10

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