Assignment Problems in Wildfire Suppression: Models for Optimization of Aerial Resource Logistics

dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Estatística, Análise Matemática e Optimizacióngl
dc.contributor.authorRodríguez Veiga, Jorge
dc.contributor.authorGómez Costa, Iván
dc.contributor.authorGinzo Villamayor, María José
dc.contributor.authorCasas Méndez, Balbina
dc.contributor.authorSáiz Díaz, José Luis
dc.date.accessioned2019-04-17T12:07:48Z
dc.date.available2019-05-22T01:00:09Z
dc.date.issued2018
dc.descriptionThis is a pre-copyedited, author-produced version of an article accepted for publication in Forest Science following peer review. The version of record Rodríguez-Veiga, J., Gómez-Costa, I., Ginzo-Villamayor, M., Casas-Méndez, B., & Sáiz-Díaz, J. (2018). Assignment Problems in Wildfire Suppression: Models for Optimization of Aerial Resource Logistics. Forest Science, 64(5), 504-514 is available online at: https://doi.org/10.1093/forsci/fxy012gl
dc.description.abstractWildfire containment activities involve a combination of important decisions that affect the evolution of the fire and effective resource deployment. When aerial resources (in particular aircraft and helicopters) are used, two tasks are assigned to the aerial coordinator: the allocation of aerial resources to flight routes (circular paths that aerial resources follow such that they have common loading and discharge points) and refueling points. In this paper, we introduce two models of linear integer programming to execute these tasks. The models are written using AMPL and the Gurobi solver engine and illustrated through examples. The objective of these models is to provide automatic and rapid support for the coordination of the abovementioned tasks. In order to enhance the robustness of the models, the scheduling times and the characteristics of the aerial resources are also considered. These models aim at minimizing both the containment time of the fire and the total flight hours. The models will reduce the risk of aerial collision of resources by taking into account the maximum number of aerial resources that can simultaneously load water at the same point. Moreover, management of refueling points is also achievedgl
dc.description.peerreviewedSIgl
dc.description.sponsorshipThis research received financial support from the Ministerio de Economía y Competitividad of Spain through grant MTM2014-53395-C3-2-P, MTM2016-76969-P, MTM2017-87197-C3-3-P, and from ITMATI, Technological Institute of Industrial Mathematics, Santiago de Compostela, Spain, through the Enjambre projectgl
dc.identifier.citationRodríguez-Veiga, J., Gómez-Costa, I., Ginzo-Villamayor, M., Casas-Méndez, B., & Sáiz-Díaz, J. (2018). Assignment Problems in Wildfire Suppression: Models for Optimization of Aerial Resource Logistics. Forest Science, 64(5), 504-514. doi: 10.1093/forsci/fxy012gl
dc.identifier.doi10.1093/forsci/fxy012
dc.identifier.essn1938-3738
dc.identifier.issn0015-749X
dc.identifier.urihttp://hdl.handle.net/10347/18646
dc.language.isoenggl
dc.publisherOxford University Pressgl
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2016-76969-P/ES
dc.relation.publisherversionhttps://doi.org/10.1093/forsci/fxy012gl
dc.rights© 2018 Society of American Foresters. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)gl
dc.rights.accessRightsopen accessgl
dc.subjectWildfire managementgl
dc.subjectAerial resources assignmentgl
dc.subjectFlight routesgl
dc.subjectRefuelinggl
dc.subjectPointsgl
dc.subjectInteger linear programminggl
dc.titleAssignment Problems in Wildfire Suppression: Models for Optimization of Aerial Resource Logisticsgl
dc.typejournal articlegl
dc.type.hasVersionAMgl
dspace.entity.typePublication
relation.isAuthorOfPublication20184528-0902-4f0d-a2e8-f7c5c4f5fff1
relation.isAuthorOfPublicationc100cb7d-00b2-441f-900b-617d886e5dee
relation.isAuthorOfPublication.latestForDiscovery20184528-0902-4f0d-a2e8-f7c5c4f5fff1

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