Getting eflcient choices in buildings by using Genetic Algorithms: assessment & validation
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.21/11704 |
Resumo: | The energy consumption in buildings, can be reduced through a rational choice of the household appliances to be acquired. This choice can be based, on a specific criteria, settled according to the consumer needs. However, such choice, still needs to be optimized, since in general, an efficient equipment has a high investment, although a low energy consumption. Genetic Algorithms (GAs) are used therefore, as an optimization technique, to get efficient and several solutions, based on those pre-selected from the market, and according to a set of criteria. However, there is a need to assess its robustness as well as its consistence in terms of convergence results. The quality of its solutions is also assessed, by comparing GAs results with those, obtained from Simplex method. The problem formulation, and its influence on GAs results, is also considered on this work, where it’s chosen the best one, among four proposed. In this paper it is presented a methodology that allows to promote energy efficiency in buildings, by achieving savings in terms of initial investment, energy consumption and CO2 emissions for the consumer. It is shown that GAs, can provide several and optimal solutions, through formulation and parameters suitable. |
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Getting eflcient choices in buildings by using Genetic Algorithms: assessment & validationEnergy efficiencyMulti-criteriaOptimizationGenetic algorithmsSimplexHousehold appliancesThe energy consumption in buildings, can be reduced through a rational choice of the household appliances to be acquired. This choice can be based, on a specific criteria, settled according to the consumer needs. However, such choice, still needs to be optimized, since in general, an efficient equipment has a high investment, although a low energy consumption. Genetic Algorithms (GAs) are used therefore, as an optimization technique, to get efficient and several solutions, based on those pre-selected from the market, and according to a set of criteria. However, there is a need to assess its robustness as well as its consistence in terms of convergence results. The quality of its solutions is also assessed, by comparing GAs results with those, obtained from Simplex method. The problem formulation, and its influence on GAs results, is also considered on this work, where it’s chosen the best one, among four proposed. In this paper it is presented a methodology that allows to promote energy efficiency in buildings, by achieving savings in terms of initial investment, energy consumption and CO2 emissions for the consumer. It is shown that GAs, can provide several and optimal solutions, through formulation and parameters suitable.De GruyterRCIPLSantos, RicardoMatias, JoãoAbreu, António2020-05-25T14:02:39Z2019-07-262019-07-26T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/11704engSANTOS, Ricardo Simões; MATIAS, João; ABREU, António – Getting eflcient choices in buildings by using genetic algorithms: assessment & validation. Open Engineering. ISSN 2391-5439. Vol. 9, N.º 1 (2019), pp. 229-2452391-5439https://doi.org/10.1515/eng-2019-0026info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-08-03T10:03:15Zoai:repositorio.ipl.pt:10400.21/11704Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:19:54.710919Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Getting eflcient choices in buildings by using Genetic Algorithms: assessment & validation |
title |
Getting eflcient choices in buildings by using Genetic Algorithms: assessment & validation |
spellingShingle |
Getting eflcient choices in buildings by using Genetic Algorithms: assessment & validation Santos, Ricardo Energy efficiency Multi-criteria Optimization Genetic algorithms Simplex Household appliances |
title_short |
Getting eflcient choices in buildings by using Genetic Algorithms: assessment & validation |
title_full |
Getting eflcient choices in buildings by using Genetic Algorithms: assessment & validation |
title_fullStr |
Getting eflcient choices in buildings by using Genetic Algorithms: assessment & validation |
title_full_unstemmed |
Getting eflcient choices in buildings by using Genetic Algorithms: assessment & validation |
title_sort |
Getting eflcient choices in buildings by using Genetic Algorithms: assessment & validation |
author |
Santos, Ricardo |
author_facet |
Santos, Ricardo Matias, João Abreu, António |
author_role |
author |
author2 |
Matias, João Abreu, António |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
RCIPL |
dc.contributor.author.fl_str_mv |
Santos, Ricardo Matias, João Abreu, António |
dc.subject.por.fl_str_mv |
Energy efficiency Multi-criteria Optimization Genetic algorithms Simplex Household appliances |
topic |
Energy efficiency Multi-criteria Optimization Genetic algorithms Simplex Household appliances |
description |
The energy consumption in buildings, can be reduced through a rational choice of the household appliances to be acquired. This choice can be based, on a specific criteria, settled according to the consumer needs. However, such choice, still needs to be optimized, since in general, an efficient equipment has a high investment, although a low energy consumption. Genetic Algorithms (GAs) are used therefore, as an optimization technique, to get efficient and several solutions, based on those pre-selected from the market, and according to a set of criteria. However, there is a need to assess its robustness as well as its consistence in terms of convergence results. The quality of its solutions is also assessed, by comparing GAs results with those, obtained from Simplex method. The problem formulation, and its influence on GAs results, is also considered on this work, where it’s chosen the best one, among four proposed. In this paper it is presented a methodology that allows to promote energy efficiency in buildings, by achieving savings in terms of initial investment, energy consumption and CO2 emissions for the consumer. It is shown that GAs, can provide several and optimal solutions, through formulation and parameters suitable. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-07-26 2019-07-26T00:00:00Z 2020-05-25T14:02:39Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.21/11704 |
url |
http://hdl.handle.net/10400.21/11704 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
SANTOS, Ricardo Simões; MATIAS, João; ABREU, António – Getting eflcient choices in buildings by using genetic algorithms: assessment & validation. Open Engineering. ISSN 2391-5439. Vol. 9, N.º 1 (2019), pp. 229-245 2391-5439 https://doi.org/10.1515/eng-2019-0026 |
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 |
De Gruyter |
publisher.none.fl_str_mv |
De Gruyter |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799133467496153088 |