The Wildfire Suppression Problem with multiple types of resources

Mualla Gonca Avci; Mustafa Avci; Maria Battarra; Güneş Erdoğan

doi:10.1016/j.ejor.2024.03.005

The Wildfire Suppression Problem with multiple types of resources

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

Research output: Contribution to journal › Article › peer-review

1 Citation (SciVal)

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.

Original language	English
Pages (from-to)	488-502
Number of pages	15
Journal	European Journal of Operational Research
Volume	316
Issue number	2
Early online date	4 Mar 2024
DOIs	https://doi.org/10.1016/j.ejor.2024.03.005
Publication status	Published - 16 Jul 2024

Funding

We would like to thank Muğla Regional Directorate of Forestry for providing the forest maps. We would like to express our gratitude to Ali Toraman from Yatağan Directorate of Forest District for sharing his expert knowledge in wildfire suppression tactics. This study has also benefited from the interviews with Rob Gazzard from the UK Forestry commission, Luke Maggs and Haf Leyshon from Natural Resources Wales and Neville Gaddes from Forestry England. The work reported in this paper was undertaken as part of the Made Smarter Innovation: Centre for People-Led Digitalisation, at the University of Bath, University of Nottingham, and Loughborough University.

Funders	Funder number
Natural Resources Wales and Neville Gaddes from Forestry England
Forestry Commission
University of Nottingham
Loughborough University

Keywords

Combinatorial Benders’ cuts
Mathematical modelling
OR in disaster relief
Wildfire suppression

ASJC Scopus subject areas

Information Systems and Management
General Computer Science
Modelling and Simulation
Management Science and Operations Research

Access to Document

10.1016/j.ejor.2024.03.005Licence: CC BY-NC-ND

Cite this

@article{4ca6c5b196a2458db567f98ff17db689,

title = "The Wildfire Suppression Problem with multiple types of resources",

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{\textquoteright} 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 T{\"u}rkiye is presented.",

keywords = "Combinatorial Benders{\textquoteright} cuts, Mathematical modelling, OR in disaster relief, Wildfire suppression",

author = "Avci, {Mualla Gonca} and Mustafa Avci and Maria Battarra and G{\"u}ne{\c s} Erdoğan",

year = "2024",

month = jul,

day = "16",

doi = "10.1016/j.ejor.2024.03.005",

language = "English",

volume = "316",

pages = "488--502",

journal = "European Journal of Operational Research",

issn = "0377-2217",

publisher = "Elsevier B.V.",

number = "2",

}

TY - JOUR

T1 - The Wildfire Suppression Problem with multiple types of resources

AU - Avci, Mualla Gonca

AU - Avci, Mustafa

AU - Battarra, Maria

AU - Erdoğan, Güneş

PY - 2024/7/16

Y1 - 2024/7/16

N2 - 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.

AB - 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.

KW - Combinatorial Benders’ cuts

KW - Mathematical modelling

KW - OR in disaster relief

KW - Wildfire suppression

UR - http://www.scopus.com/inward/record.url?scp=85186657092&partnerID=8YFLogxK

U2 - 10.1016/j.ejor.2024.03.005

DO - 10.1016/j.ejor.2024.03.005

M3 - Article

SN - 0377-2217

VL - 316

SP - 488

EP - 502

JO - European Journal of Operational Research

JF - European Journal of Operational Research

IS - 2

ER -

The Wildfire Suppression Problem with multiple types of resources

Abstract

Funding

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Made Smarter Innovation - People-Led Digitalisation

Cite this

The Wildfire Suppression Problem with multiple types of resources

Abstract

Funding

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Projects

Made Smarter Innovation - People-Led Digitalisation

Cite this