Dependency structure matrix, genetic algorithms, and effective recombination
Autor(a) principal: | |
---|---|
Data de Publicação: | 2009 |
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/10400.1/11961 |
Resumo: | In many different fields, researchers are often confronted by problems arising from complex systems. Simple heuristics or even enumeration works quite well on small and easy problems; however, to efficiently solve large and difficult problems, proper decomposition is the key. In this paper, investigating and analyzing interactions between components of complex systems shed some light on problem decomposition. By recognizing three bare-bones interactions-modularity, hierarchy, and overlap, facet-wise models arc developed to dissect and inspect problem decomposition in the context of genetic algorithms. The proposed genetic algorithm design utilizes a matrix representation of an interaction graph to analyze and explicitly decompose the problem. The results from this paper should benefit research both technically and scientifically. Technically, this paper develops an automated dependency structure matrix clustering technique and utilizes it to design a model-building genetic algorithm that learns and delivers the problem structure. Scientifically, the explicit interaction model describes the problem structure very well and helps researchers gain important insights through the explicitness of the procedure. |
id |
RCAP_2af28194639783de4a648507359522be |
---|---|
oai_identifier_str |
oai:sapientia.ualg.pt:10400.1/11961 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
Dependency structure matrix, genetic algorithms, and effective recombinationProduct developmentInformationPrincipleIn many different fields, researchers are often confronted by problems arising from complex systems. Simple heuristics or even enumeration works quite well on small and easy problems; however, to efficiently solve large and difficult problems, proper decomposition is the key. In this paper, investigating and analyzing interactions between components of complex systems shed some light on problem decomposition. By recognizing three bare-bones interactions-modularity, hierarchy, and overlap, facet-wise models arc developed to dissect and inspect problem decomposition in the context of genetic algorithms. The proposed genetic algorithm design utilizes a matrix representation of an interaction graph to analyze and explicitly decompose the problem. The results from this paper should benefit research both technically and scientifically. Technically, this paper develops an automated dependency structure matrix clustering technique and utilizes it to design a model-building genetic algorithm that learns and delivers the problem structure. Scientifically, the explicit interaction model describes the problem structure very well and helps researchers gain important insights through the explicitness of the procedure.This work was sponsored by Taiwan National Science Council under grant NSC97- 2218-E-002-020-MY3, U.S. Air Force Office of Scientific Research, Air Force Material Command, USAF, under grants FA9550-06-1-0370 and FA9550-06-1-0096, U.S. National Science Foundation under CAREER grant ECS-0547013, ITR grant DMR-03-25939 at Materials Computation Center, grant ISS-02-09199 at US National Center for Supercomputing Applications, UIUC, and the Portuguese Foundation for Science and Technology under grants SFRH/BD/16980/2004 and PTDC/EIA/67776/2006.Massachusetts Institute of Technology PressSapientiaYu, Tian-LiGoldberg, David E.Sastry, KumaraLima, Claudio F.Pelikan, Martin2018-12-07T14:58:19Z2009-122009-12-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.1/11961eng1063-6560https://doi.org/10.1162/evco.2009.17.4.17409info: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:RCAAP2023-07-24T10:23:52Zoai:sapientia.ualg.pt:10400.1/11961Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:03:23.692984Repositório 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 |
Dependency structure matrix, genetic algorithms, and effective recombination |
title |
Dependency structure matrix, genetic algorithms, and effective recombination |
spellingShingle |
Dependency structure matrix, genetic algorithms, and effective recombination Yu, Tian-Li Product development Information Principle |
title_short |
Dependency structure matrix, genetic algorithms, and effective recombination |
title_full |
Dependency structure matrix, genetic algorithms, and effective recombination |
title_fullStr |
Dependency structure matrix, genetic algorithms, and effective recombination |
title_full_unstemmed |
Dependency structure matrix, genetic algorithms, and effective recombination |
title_sort |
Dependency structure matrix, genetic algorithms, and effective recombination |
author |
Yu, Tian-Li |
author_facet |
Yu, Tian-Li Goldberg, David E. Sastry, Kumara Lima, Claudio F. Pelikan, Martin |
author_role |
author |
author2 |
Goldberg, David E. Sastry, Kumara Lima, Claudio F. Pelikan, Martin |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Sapientia |
dc.contributor.author.fl_str_mv |
Yu, Tian-Li Goldberg, David E. Sastry, Kumara Lima, Claudio F. Pelikan, Martin |
dc.subject.por.fl_str_mv |
Product development Information Principle |
topic |
Product development Information Principle |
description |
In many different fields, researchers are often confronted by problems arising from complex systems. Simple heuristics or even enumeration works quite well on small and easy problems; however, to efficiently solve large and difficult problems, proper decomposition is the key. In this paper, investigating and analyzing interactions between components of complex systems shed some light on problem decomposition. By recognizing three bare-bones interactions-modularity, hierarchy, and overlap, facet-wise models arc developed to dissect and inspect problem decomposition in the context of genetic algorithms. The proposed genetic algorithm design utilizes a matrix representation of an interaction graph to analyze and explicitly decompose the problem. The results from this paper should benefit research both technically and scientifically. Technically, this paper develops an automated dependency structure matrix clustering technique and utilizes it to design a model-building genetic algorithm that learns and delivers the problem structure. Scientifically, the explicit interaction model describes the problem structure very well and helps researchers gain important insights through the explicitness of the procedure. |
publishDate |
2009 |
dc.date.none.fl_str_mv |
2009-12 2009-12-01T00:00:00Z 2018-12-07T14:58:19Z |
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/10400.1/11961 |
url |
http://hdl.handle.net/10400.1/11961 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1063-6560 https://doi.org/10.1162/evco.2009.17.4.17409 |
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 |
Massachusetts Institute of Technology Press |
publisher.none.fl_str_mv |
Massachusetts Institute of Technology Press |
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 |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
|
_version_ |
1799133268031832064 |