A bi-objective optimization approach for wildfire detection

Bibliographic Details
Main Author: Alvelos, Filipe Pereira e
Publication Date: 2023
Other Authors: Santos, Sarah Moura Batista, Vieira, António, Bento-Gonçalves, António
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: https://hdl.handle.net/1822/89806
Summary: We consider the problem of buying and locating equipment for covering a (discretized) region. We propose two approaches, based on mathematical programming modelling and the epsilon-constraint method, that allow obtaining the efficient frontier of a bi-objective optimization problem. In the first approach, the objectives are maximizing coverage and minimizing cost. In the second approach, lexicographic optimization is used to incorporate additional objectives - maximizing double coverage and minimizing the maximum fire rate of spread of uncovered points. The latter objective comes from the specific application that motivated this work: wildfire detection. We present results from a case study in a portuguese landscape, as an example of the potential of optimization models and methods to support decision making in such a relevant field.
id RCAP_9261cd3ce03ad3c601f14d3d444782d2
oai_identifier_str oai:repositorium.sdum.uminho.pt:1822/89806
network_acronym_str RCAP
network_name_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository_id_str https://opendoar.ac.uk/repository/7160
spelling A bi-objective optimization approach for wildfire detectionLocationMulti-objective optimizationWildfire detectionWe consider the problem of buying and locating equipment for covering a (discretized) region. We propose two approaches, based on mathematical programming modelling and the epsilon-constraint method, that allow obtaining the efficient frontier of a bi-objective optimization problem. In the first approach, the objectives are maximizing coverage and minimizing cost. In the second approach, lexicographic optimization is used to incorporate additional objectives - maximizing double coverage and minimizing the maximum fire rate of spread of uncovered points. The latter objective comes from the specific application that motivated this work: wildfire detection. We present results from a case study in a portuguese landscape, as an example of the potential of optimization models and methods to support decision making in such a relevant field.This research was supported by FCT- Fundação para a Ciência e Tecnologia , within the scope of project “O3F- An Optimization Framework to reduce Forest Fire”- PCIF/GRF/0141/2019. We also acknowledge the Municipality of Baião and the Volunteer Firefighters of Baião and Sta. Marinha do Zˆezere for the constant support and for accompanying in the technical and field visits to Baião.Springer/Springer LinkUniversidade do MinhoAlvelos, Filipe Pereira eSantos, Sarah Moura BatistaVieira, AntónioBento-Gonçalves, António20232023-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/1822/89806engAlvelos, F., Moura, S., Vieira, A., Bento-Gonçalves, A. (2023). A Bi-objective Optimization Approach for Wildfire Detection. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2023 Workshops. ICCSA 2023. Lecture Notes in Computer Science, vol 14105. Springer, Cham. https://doi.org/10.1007/978-3-031-37108-0_27978-3-031-37107-30302-97431611-334910.1007/978-3-031-37108-0_27978-3-031-37108-0https://link.springer.com/chapter/10.1007/978-3-031-37108-0_27info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T06:50:52Zoai:repositorium.sdum.uminho.pt:1822/89806Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T16:06:15.809257Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv A bi-objective optimization approach for wildfire detection
title A bi-objective optimization approach for wildfire detection
spellingShingle A bi-objective optimization approach for wildfire detection
Alvelos, Filipe Pereira e
Location
Multi-objective optimization
Wildfire detection
title_short A bi-objective optimization approach for wildfire detection
title_full A bi-objective optimization approach for wildfire detection
title_fullStr A bi-objective optimization approach for wildfire detection
title_full_unstemmed A bi-objective optimization approach for wildfire detection
title_sort A bi-objective optimization approach for wildfire detection
author Alvelos, Filipe Pereira e
author_facet Alvelos, Filipe Pereira e
Santos, Sarah Moura Batista
Vieira, António
Bento-Gonçalves, António
author_role author
author2 Santos, Sarah Moura Batista
Vieira, António
Bento-Gonçalves, António
author2_role author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Alvelos, Filipe Pereira e
Santos, Sarah Moura Batista
Vieira, António
Bento-Gonçalves, António
dc.subject.por.fl_str_mv Location
Multi-objective optimization
Wildfire detection
topic Location
Multi-objective optimization
Wildfire detection
description We consider the problem of buying and locating equipment for covering a (discretized) region. We propose two approaches, based on mathematical programming modelling and the epsilon-constraint method, that allow obtaining the efficient frontier of a bi-objective optimization problem. In the first approach, the objectives are maximizing coverage and minimizing cost. In the second approach, lexicographic optimization is used to incorporate additional objectives - maximizing double coverage and minimizing the maximum fire rate of spread of uncovered points. The latter objective comes from the specific application that motivated this work: wildfire detection. We present results from a case study in a portuguese landscape, as an example of the potential of optimization models and methods to support decision making in such a relevant field.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-01-01T00:00:00Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://hdl.handle.net/1822/89806
url https://hdl.handle.net/1822/89806
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Alvelos, F., Moura, S., Vieira, A., Bento-Gonçalves, A. (2023). A Bi-objective Optimization Approach for Wildfire Detection. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2023 Workshops. ICCSA 2023. Lecture Notes in Computer Science, vol 14105. Springer, Cham. https://doi.org/10.1007/978-3-031-37108-0_27
978-3-031-37107-3
0302-9743
1611-3349
10.1007/978-3-031-37108-0_27
978-3-031-37108-0
https://link.springer.com/chapter/10.1007/978-3-031-37108-0_27
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer/Springer Link
publisher.none.fl_str_mv Springer/Springer Link
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
_version_ 1833595740504457216

Similar Items