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Evolutionary algorithms on reducing energy consumption in buildings: An approach to provide smart and efficiency choices, considering the rebound effect

2018-12Journal article Restricted access
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dc.contributor.authorSantos, Ricardo
dc.contributor.authorMatias, João
dc.contributor.authorAbreu, António
dc.contributor.authorReis, Francisco
dc.date.accessioned2019-01-18T10:34:45Z
dc.date.available2019-01-18T10:34:45Z
dc.date.issued2018-12
dc.description.abstractThis paper presents a model to promote energy efficiency among household appliances, by supporting the consumer decisions through the maximization of his savings, associated to a set of electrical appliances from the market to be acquired. Not always an efficient equipment from the market, is more expensive than a less efficient one, which can lead the consumer to compromise the expected savings on future. Given the several models/brands available on market and its possible combinations, the problem can be defined as a combinatorial problem, whose complexity can compromise the efficiency of using deterministic algorithms. Genetic algorithms (GM) were therefore included in the model, whose results were compared later with Simplex to verify the quality of the obtained solutions, as well as their performance. In addition, it was performed a statistical analysis of the obtained results, as well as a sensitivity analysis of GAs parameters, to validate their robustness. we conclude that the proposed method can provide several efficient solutions to the problem, as well as sensitize the consumer to their choices made on future, by estimating their corresponding rebound effect.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSANTOS, Ricardo; [et al] – Evolutionary algorithms on reducing energy consumption in buildings: An approach to provide smart and efficiency choices, considering the rebound effect. Computers and Industrial Engineering. ISSN 0360-8352. Vol. 126 (2018), pp. 729-755pt_PT
dc.identifier.doi10.1016/j.cie.2018.09.050pt_PT
dc.identifier.issn0360-8352
dc.identifier.urihttp://hdl.handle.net/10400.21/9345
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relation.publisherversionhttps://reader.elsevier.com/reader/sd/pii/S0360835218304662?token=2A55CCC1A97776039AB80AFC523BB28C9E7E69175B699492ADBEAEBDC22A5D1AE63EC548E26951B5F6D035B83D270C59pt_PT
dc.subjectEnergy efficiencypt_PT
dc.subjectGenetic algorithms (GAs)pt_PT
dc.subjectSimplex methodpt_PT
dc.subjectLife Cycle Cost Analysis (LCCA)pt_PT
dc.subjectIndirect Rebound Effectpt_PT
dc.titleEvolutionary algorithms on reducing energy consumption in buildings: An approach to provide smart and efficiency choices, considering the rebound effectpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage755pt_PT
oaire.citation.startPage729pt_PT
oaire.citation.titleComputers and Industrial Engineeringpt_PT
oaire.citation.volume126pt_PT
person.familyNameSantos
person.familyNameMatias
person.familyNameAbreu
person.givenNameRicardo
person.givenNameJoao
person.givenNameAntónio
person.identifier1829666
person.identifier.ciencia-idC213-A238-5F53
person.identifier.ciencia-idD610-9D89-C48F
person.identifier.ciencia-idF51F-F42E-3D57
person.identifier.orcid0000-0001-5703-8139
person.identifier.orcid0000-0003-4329-6246
person.identifier.orcid0000-0001-8839-5606
person.identifier.ridM-9354-2018
person.identifier.ridT-9007-2017
person.identifier.ridD-3964-2014
person.identifier.scopus-author-id56015094400
person.identifier.scopus-author-id57218315486
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication9312aee8-32f1-4907-966d-be2dc485f975
relation.isAuthorOfPublication9d0d968b-bf76-431a-99fe-aeae428faa28
relation.isAuthorOfPublication2e303e99-df37-4381-bf3c-0ab7fc69703c
relation.isAuthorOfPublication.latestForDiscovery2e303e99-df37-4381-bf3c-0ab7fc69703c

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