Aggregation Trees for visualization and dimension reduction in many-objective optimization.

Detalhes bibliográficos
Autor(a) principal: Freitas, Alan Robert Resende de
Data de Publicação: 2015
Outros Autores: Fleming, Peter J., Guimarães, Frederico Gadelha
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFOP
Texto Completo: http://www.repositorio.ufop.br/handle/123456789/4293
https://doi.org/10.1016/j.ins.2014.11.044
Resumo: This paper introduces the concept of Aggregation Trees for the visualization of the results of high-dimensional multi-objective optimization problems, or many-objective problems and as a means of performing dimension reduction. The high dimensionality of manyobjective optimization makes it difficult to represent the relationship between objectives and solutions in such problems and most approaches in the literature are based on the representation of solutions in lower dimensions. The method of Aggregation Trees proposed here is based on an iterative aggregation of objectives that are represented in a tree. The location of conflict is also calculated and represented on the tree. Thus, the tree can represent which objectives and groups of objectives are the most harmonic, what sort of conflict is present between groups of objectives, and which aggregations would be helpful in order to reduce the problem dimension.
id UFOP_e7e59214127cfa3ee0cc346d1a39cda6
oai_identifier_str oai:localhost:123456789/4293
network_acronym_str UFOP
network_name_str Repositório Institucional da UFOP
repository_id_str 3233
spelling Freitas, Alan Robert Resende deFleming, Peter J.Guimarães, Frederico Gadelha2015-01-21T17:59:37Z2015-01-21T17:59:37Z2015FREITAS, A. R. R. de.; FLEMING, P. J.; GUIMARÃES, F. G. Aggregation Trees for visualization and dimension reduction in many-objective optimization. Information Sciences, v. 298, p. 288-314, 2015. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0020025514011347#>. Acesso em: 21 jan. 2015.0020-0255http://www.repositorio.ufop.br/handle/123456789/4293https://doi.org/10.1016/j.ins.2014.11.044This paper introduces the concept of Aggregation Trees for the visualization of the results of high-dimensional multi-objective optimization problems, or many-objective problems and as a means of performing dimension reduction. The high dimensionality of manyobjective optimization makes it difficult to represent the relationship between objectives and solutions in such problems and most approaches in the literature are based on the representation of solutions in lower dimensions. The method of Aggregation Trees proposed here is based on an iterative aggregation of objectives that are represented in a tree. The location of conflict is also calculated and represented on the tree. Thus, the tree can represent which objectives and groups of objectives are the most harmonic, what sort of conflict is present between groups of objectives, and which aggregations would be helpful in order to reduce the problem dimension.Aggregation treesEvolutionary computationAggregation Trees for visualization and dimension reduction in many-objective optimization.info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleO periódico Information Sciences concede permissão para depósito do artigo no Repositório Institucional da UFOP. Número da licença: 3552540146011.info:eu-repo/semantics/openAccessengreponame:Repositório Institucional da UFOPinstname:Universidade Federal de Ouro Preto (UFOP)instacron:UFOPLICENSElicense.txtlicense.txttext/plain; charset=utf-82636http://www.repositorio.ufop.br/bitstream/123456789/4293/2/license.txtc2ffdd99e58acf69202dff00d361f23aMD52ORIGINALARTIGO_AggregationTreesVsualization.pdfARTIGO_AggregationTreesVsualization.pdfapplication/pdf1990167http://www.repositorio.ufop.br/bitstream/123456789/4293/1/ARTIGO_AggregationTreesVsualization.pdf0d39e1f2adcd16eb2b2306e22189d750MD51123456789/42932019-06-11 12:14:02.066oai:localhost: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Repositório InstitucionalPUBhttp://www.repositorio.ufop.br/oai/requestrepositorio@ufop.edu.bropendoar:32332019-06-11T16:14:02Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)false
dc.title.pt_BR.fl_str_mv Aggregation Trees for visualization and dimension reduction in many-objective optimization.
title Aggregation Trees for visualization and dimension reduction in many-objective optimization.
spellingShingle Aggregation Trees for visualization and dimension reduction in many-objective optimization.
Freitas, Alan Robert Resende de
Aggregation trees
Evolutionary computation
title_short Aggregation Trees for visualization and dimension reduction in many-objective optimization.
title_full Aggregation Trees for visualization and dimension reduction in many-objective optimization.
title_fullStr Aggregation Trees for visualization and dimension reduction in many-objective optimization.
title_full_unstemmed Aggregation Trees for visualization and dimension reduction in many-objective optimization.
title_sort Aggregation Trees for visualization and dimension reduction in many-objective optimization.
author Freitas, Alan Robert Resende de
author_facet Freitas, Alan Robert Resende de
Fleming, Peter J.
Guimarães, Frederico Gadelha
author_role author
author2 Fleming, Peter J.
Guimarães, Frederico Gadelha
author2_role author
author
dc.contributor.author.fl_str_mv Freitas, Alan Robert Resende de
Fleming, Peter J.
Guimarães, Frederico Gadelha
dc.subject.por.fl_str_mv Aggregation trees
Evolutionary computation
topic Aggregation trees
Evolutionary computation
description This paper introduces the concept of Aggregation Trees for the visualization of the results of high-dimensional multi-objective optimization problems, or many-objective problems and as a means of performing dimension reduction. The high dimensionality of manyobjective optimization makes it difficult to represent the relationship between objectives and solutions in such problems and most approaches in the literature are based on the representation of solutions in lower dimensions. The method of Aggregation Trees proposed here is based on an iterative aggregation of objectives that are represented in a tree. The location of conflict is also calculated and represented on the tree. Thus, the tree can represent which objectives and groups of objectives are the most harmonic, what sort of conflict is present between groups of objectives, and which aggregations would be helpful in order to reduce the problem dimension.
publishDate 2015
dc.date.accessioned.fl_str_mv 2015-01-21T17:59:37Z
dc.date.available.fl_str_mv 2015-01-21T17:59:37Z
dc.date.issued.fl_str_mv 2015
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.citation.fl_str_mv FREITAS, A. R. R. de.; FLEMING, P. J.; GUIMARÃES, F. G. Aggregation Trees for visualization and dimension reduction in many-objective optimization. Information Sciences, v. 298, p. 288-314, 2015. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0020025514011347#>. Acesso em: 21 jan. 2015.
dc.identifier.uri.fl_str_mv http://www.repositorio.ufop.br/handle/123456789/4293
dc.identifier.issn.none.fl_str_mv 0020-0255
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1016/j.ins.2014.11.044
identifier_str_mv FREITAS, A. R. R. de.; FLEMING, P. J.; GUIMARÃES, F. G. Aggregation Trees for visualization and dimension reduction in many-objective optimization. Information Sciences, v. 298, p. 288-314, 2015. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0020025514011347#>. Acesso em: 21 jan. 2015.
0020-0255
url http://www.repositorio.ufop.br/handle/123456789/4293
https://doi.org/10.1016/j.ins.2014.11.044
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFOP
instname:Universidade Federal de Ouro Preto (UFOP)
instacron:UFOP
instname_str Universidade Federal de Ouro Preto (UFOP)
instacron_str UFOP
institution UFOP
reponame_str Repositório Institucional da UFOP
collection Repositório Institucional da UFOP
bitstream.url.fl_str_mv http://www.repositorio.ufop.br/bitstream/123456789/4293/2/license.txt
http://www.repositorio.ufop.br/bitstream/123456789/4293/1/ARTIGO_AggregationTreesVsualization.pdf
bitstream.checksum.fl_str_mv c2ffdd99e58acf69202dff00d361f23a
0d39e1f2adcd16eb2b2306e22189d750
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
repository.name.fl_str_mv Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)
repository.mail.fl_str_mv repositorio@ufop.edu.br
_version_ 1801685731872079872