A Genetic Algorithm to Obtain Consistency in Analytic Hierarchy Process
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Brazilian Journal of Operations & Production Management (Online) |
Texto Completo: | https://bjopm.org.br/bjopm/article/view/V8N1A4 |
Resumo: | This work presents a proposition to solve the problem of inconsistency in Analytic HierarchyProcess (AHP) matrices using genetic algorithms. Decision matrices resulting from an applicationof AHP can be considered an effective method to structure and represent relevant information ofa strategic problem. Inconsistency in the results is a real and frequent possibility. In this case, theresults obtained would become ineffective considering the objectives of the model, which meansno gains in decision making. The Genetic Algorithms are probabilistic search computer modelswhich are based on the mechanics of natural selection and genetics, combining the concepts ofselective adaptation and survival of the fittest. They are considered to be a powerful technique ofstochastic optimization and, probably the most important evolutionary computer techniques. Itsapplication to the AHP matrices case allows the detection of inconsistent matrices, while offersalternative solutions to the decision-maker. |
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Brazilian Journal of Operations & Production Management (Online) |
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A Genetic Algorithm to Obtain Consistency in Analytic Hierarchy ProcessAHPInconsistent MatricesGenetic Algorithms This work presents a proposition to solve the problem of inconsistency in Analytic HierarchyProcess (AHP) matrices using genetic algorithms. Decision matrices resulting from an applicationof AHP can be considered an effective method to structure and represent relevant information ofa strategic problem. Inconsistency in the results is a real and frequent possibility. In this case, theresults obtained would become ineffective considering the objectives of the model, which meansno gains in decision making. The Genetic Algorithms are probabilistic search computer modelswhich are based on the mechanics of natural selection and genetics, combining the concepts ofselective adaptation and survival of the fittest. They are considered to be a powerful technique ofstochastic optimization and, probably the most important evolutionary computer techniques. Itsapplication to the AHP matrices case allows the detection of inconsistent matrices, while offersalternative solutions to the decision-maker. Brazilian Association for Industrial Engineering and Operations Management (ABEPRO)2011-12-19info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer-reviewed ArticleAHP; Genetic Algorithms;application/pdfapplication/mswordhttps://bjopm.org.br/bjopm/article/view/V8N1A4Brazilian Journal of Operations & Production Management; Vol. 8 No. 1 (2011): July, 2011; 55-642237-8960reponame:Brazilian Journal of Operations & Production Management (Online)instname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPROenghttps://bjopm.org.br/bjopm/article/view/V8N1A4/V8N1A4https://bjopm.org.br/bjopm/article/view/V8N1A4/375da Serra Costa, José Fabianoinfo:eu-repo/semantics/openAccess2019-04-04T07:28:45Zoai:ojs.bjopm.org.br:article/113Revistahttps://bjopm.org.br/bjopmONGhttps://bjopm.org.br/bjopm/oaibjopm.journal@gmail.com2237-89601679-8171opendoar:2023-03-13T09:45:04.749059Brazilian Journal of Operations & Production Management (Online) - Associação Brasileira de Engenharia de Produção (ABEPRO)false |
dc.title.none.fl_str_mv |
A Genetic Algorithm to Obtain Consistency in Analytic Hierarchy Process |
title |
A Genetic Algorithm to Obtain Consistency in Analytic Hierarchy Process |
spellingShingle |
A Genetic Algorithm to Obtain Consistency in Analytic Hierarchy Process da Serra Costa, José Fabiano AHP Inconsistent Matrices Genetic Algorithms |
title_short |
A Genetic Algorithm to Obtain Consistency in Analytic Hierarchy Process |
title_full |
A Genetic Algorithm to Obtain Consistency in Analytic Hierarchy Process |
title_fullStr |
A Genetic Algorithm to Obtain Consistency in Analytic Hierarchy Process |
title_full_unstemmed |
A Genetic Algorithm to Obtain Consistency in Analytic Hierarchy Process |
title_sort |
A Genetic Algorithm to Obtain Consistency in Analytic Hierarchy Process |
author |
da Serra Costa, José Fabiano |
author_facet |
da Serra Costa, José Fabiano |
author_role |
author |
dc.contributor.author.fl_str_mv |
da Serra Costa, José Fabiano |
dc.subject.por.fl_str_mv |
AHP Inconsistent Matrices Genetic Algorithms |
topic |
AHP Inconsistent Matrices Genetic Algorithms |
description |
This work presents a proposition to solve the problem of inconsistency in Analytic HierarchyProcess (AHP) matrices using genetic algorithms. Decision matrices resulting from an applicationof AHP can be considered an effective method to structure and represent relevant information ofa strategic problem. Inconsistency in the results is a real and frequent possibility. In this case, theresults obtained would become ineffective considering the objectives of the model, which meansno gains in decision making. The Genetic Algorithms are probabilistic search computer modelswhich are based on the mechanics of natural selection and genetics, combining the concepts ofselective adaptation and survival of the fittest. They are considered to be a powerful technique ofstochastic optimization and, probably the most important evolutionary computer techniques. Itsapplication to the AHP matrices case allows the detection of inconsistent matrices, while offersalternative solutions to the decision-maker. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-12-19 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article AHP; Genetic Algorithms; |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://bjopm.org.br/bjopm/article/view/V8N1A4 |
url |
https://bjopm.org.br/bjopm/article/view/V8N1A4 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://bjopm.org.br/bjopm/article/view/V8N1A4/V8N1A4 https://bjopm.org.br/bjopm/article/view/V8N1A4/375 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/msword |
dc.publisher.none.fl_str_mv |
Brazilian Association for Industrial Engineering and Operations Management (ABEPRO) |
publisher.none.fl_str_mv |
Brazilian Association for Industrial Engineering and Operations Management (ABEPRO) |
dc.source.none.fl_str_mv |
Brazilian Journal of Operations & Production Management; Vol. 8 No. 1 (2011): July, 2011; 55-64 2237-8960 reponame:Brazilian Journal of Operations & Production Management (Online) instname:Associação Brasileira de Engenharia de Produção (ABEPRO) instacron:ABEPRO |
instname_str |
Associação Brasileira de Engenharia de Produção (ABEPRO) |
instacron_str |
ABEPRO |
institution |
ABEPRO |
reponame_str |
Brazilian Journal of Operations & Production Management (Online) |
collection |
Brazilian Journal of Operations & Production Management (Online) |
repository.name.fl_str_mv |
Brazilian Journal of Operations & Production Management (Online) - Associação Brasileira de Engenharia de Produção (ABEPRO) |
repository.mail.fl_str_mv |
bjopm.journal@gmail.com |
_version_ |
1797051460009066496 |