A Mathematical Programming Approach for a Wildfire Suppression Problem

Wildfires are natural recurrent events, that may be devastating if not addressed correctly. In these situations, where quick and accurate decisions are needed, Operations Research can be helpful for providing fast and robust solutions. This paper focuses on the response actions taken during the supp...

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Detalles Bibliográficos
Autores: Granda Chico, Bibiana, Vitoriano Villanueva, Begoña, Figueira, José R.
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/104710
Acceso en línea:https://hdl.handle.net/20.500.14352/104710
Access Level:acceso abierto
Palabra clave:Wildfire management
Wildfire suppression
Optimization
Mixed Integer Linear Programming
Investigación operativa (Matemáticas)
1207.07 Programación Entera
Descripción
Sumario:Wildfires are natural recurrent events, that may be devastating if not addressed correctly. In these situations, where quick and accurate decisions are needed, Operations Research can be helpful for providing fast and robust solutions. This paper focuses on the response actions taken during the suppression stage of a wildfire. A mixed integer linear programming model is proposed to obtain a wildfire suppression strategy, including the wildfire behaviour changes induced by the solution. The selected wildfire suppression strategy is modelled in detail, pointing out which locations to control and their timing, based on available paths between them, avoiding engagement in dangerous situations. A computational study is carried out to determine the most suitable solver to provide exact solutions of the model. Also, a two-stage version of the model is proposed to deal with the multicriteria nature of the problem. A case study is also included to validate the model’s applicability, which is solved using the two proposed versions of the model and an iterative approach to compare their performance.