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Fire Risk Reduction and Recover Energy Potential: A Disruptive Theoretical Optimization Model to the Residual Biomass Supply Chain

dc.contributor.authorBastos, Tiago
dc.contributor.authorTeixeira, Leonor
dc.contributor.authorNunes, Leonel J. R.
dc.date.accessioned2025-08-08T11:34:01Z
dc.date.available2025-08-08T11:34:01Z
dc.date.issued2024-07
dc.description.abstractRural fires have been a constant concern, with most being associated with land abandon- ment. However, some fires occur due to negligent attitudes towards fire, which is often used to remove agroforestry leftovers. In addition to the fire risk, this burning also represents a waste of the energy present in this residual biomass. Both rural fires and energy waste affect the three dimensions of sustainability. The ideal solution seems to be to use this biomass, avoiding the need for burning and recovering the energy potential. However, this process is strongly affected by logistical costs, making this recovery unfeasible. In this context, this study aims to propose an optimization model for this chain, focusing on the three dimensions of sustainability. The results of the present study comprise a summary of the current state of the art in supply-chain optimization, as well as a disrup- tive mathematical model to optimize the residual biomass supply chain. To achieve this objective, a literature review was carried out in the first phase, incorporating the specificities of the context under study to arrive at the final model. To conclude, this study provides a review covering several metaheuristics, including ant colony optimization, genetic algorithms, particle swarm optimization, and simulated annealing, which can be used in this context, adding another valuable input to the final discussion.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationBastos, T.; Teixeira, L.; Nunes, L.J.R. Fire Risk Reduction and Recover Energy Potential: A Disruptive Theoretical Optimization Model to the Residual Biomass Supply Chain. Fire 2024, 7, 263. https://doi.org/10.3390/fire7080263pt_PT
dc.identifier.doi10.3390/fire7080263pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.5/102736
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherMDPIpt_PT
dc.relation.publisherversionhttps://www.mdpi.com/journal/firept_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectresidual biomass supply chainpt_PT
dc.subjectoptimization modelpt_PT
dc.subjectsustainabilitypt_PT
dc.subjectenergy recoverypt_PT
dc.subjectagroforestry biomasspt_PT
dc.titleFire Risk Reduction and Recover Energy Potential: A Disruptive Theoretical Optimization Model to the Residual Biomass Supply Chainpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/Concurso de Projetos de Investigação Científica e Desenvolvimento Tecnológico no Âmbito da Prevenção e Combate a Incêndios Florestais - 2019/PCIF%2FGVB%2F0083%2F2019/PT
oaire.citation.issue8pt_PT
oaire.citation.startPage263pt_PT
oaire.citation.titleFirept_PT
oaire.citation.volume7pt_PT
oaire.fundingStreamConcurso de Projetos de Investigação Científica e Desenvolvimento Tecnológico no Âmbito da Prevenção e Combate a Incêndios Florestais - 2019
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isProjectOfPublicationb7ede676-bae8-4c3c-9765-54f3a6838b2a
relation.isProjectOfPublication.latestForDiscoveryb7ede676-bae8-4c3c-9765-54f3a6838b2a

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