On Challenging Techniques for Constrained Global Optimization
Autor(a) principal: | |
---|---|
Data de Publicação: | 2013 |
Outros Autores: | , , , |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/50105 |
Resumo: | This chapter aims to address the challenging and demanding issue of solving a continuous nonlinear constrained global optimization problem. We propose four stochastic methods that rely on a population of points to diversify the search for a global solution: genetic algorithm, differential evolution, artificial fish swarm algorithm and electromagnetism-like mechanism. The performance of different variants of these algorithms is analyzed using a benchmark set of problems. Three different strategies to handle the equality and inequality constraints of the problem are addressed. An augmented Lagrangian-based technique, the tournament selection based on feasibility and dominance rules, and a strategy based on ranking objective and constraint violation are presented and tested. Numerical experiments are reported showing the effectiveness of our suggestions. Two well-known engineering design problems are successfully solved by the proposed methods. © Springer-Verlag Berlin Heidelberg 2013. |
id |
RCAP_35869a4208364200d4fcf79efb8265d0 |
---|---|
oai_identifier_str |
oai:repositorium.sdum.uminho.pt:1822/50105 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
On Challenging Techniques for Constrained Global OptimizationCiências Naturais::Ciências da Computação e da InformaçãoThis chapter aims to address the challenging and demanding issue of solving a continuous nonlinear constrained global optimization problem. We propose four stochastic methods that rely on a population of points to diversify the search for a global solution: genetic algorithm, differential evolution, artificial fish swarm algorithm and electromagnetism-like mechanism. The performance of different variants of these algorithms is analyzed using a benchmark set of problems. Three different strategies to handle the equality and inequality constraints of the problem are addressed. An augmented Lagrangian-based technique, the tournament selection based on feasibility and dominance rules, and a strategy based on ranking objective and constraint violation are presented and tested. Numerical experiments are reported showing the effectiveness of our suggestions. Two well-known engineering design problems are successfully solved by the proposed methods. © Springer-Verlag Berlin Heidelberg 2013.Fundação para a Ciência e a Tecnologia (Foundation for Science and Technology), Portugal for the financial support under fellowship grant: C2007-UMINHO-ALGORITMI-04. The other authors acknowledge FEDER COMPETE, Programa Operacional Fatores de Competitividade (Operational Programme Thematic Factors of Competitiveness) and FCT for the financial support under project grant: FCOMP-01-0124-FEDER-022674info:eu-repo/semantics/publishedVersionSpringer VerlagUniversidade do MinhoEspírito Santo, I. A. C. P.Costa, LinoRocha, Ana Maria A. C.Azad, Md. Abul KalamFernandes, Edite Manuela da G. P.2013-10-182013-10-18T00:00:00Zbook partinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/50105engSanto, I. A. E., Costa, L., Rocha, A. M. A., Azad, M. A. K., & Fernandes, E. M. (2013). On challenging techniques for constrained global optimization. In Handbook of Optimization (pp. 641-671). Springer, Berlin, Heidelberg978-3-642-30503-01868-439410.1007/978-3-642-30504-7_26978-3-642-30504-7https://link.springer.com/chapter/10.1007/978-3-642-30504-7_26info: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:RCAAP2024-05-11T05:19:24Zoai:repositorium.sdum.uminho.pt:1822/50105Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-11T05:19:24Repositório 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 |
On Challenging Techniques for Constrained Global Optimization |
title |
On Challenging Techniques for Constrained Global Optimization |
spellingShingle |
On Challenging Techniques for Constrained Global Optimization Espírito Santo, I. A. C. P. Ciências Naturais::Ciências da Computação e da Informação |
title_short |
On Challenging Techniques for Constrained Global Optimization |
title_full |
On Challenging Techniques for Constrained Global Optimization |
title_fullStr |
On Challenging Techniques for Constrained Global Optimization |
title_full_unstemmed |
On Challenging Techniques for Constrained Global Optimization |
title_sort |
On Challenging Techniques for Constrained Global Optimization |
author |
Espírito Santo, I. A. C. P. |
author_facet |
Espírito Santo, I. A. C. P. Costa, Lino Rocha, Ana Maria A. C. Azad, Md. Abul Kalam Fernandes, Edite Manuela da G. P. |
author_role |
author |
author2 |
Costa, Lino Rocha, Ana Maria A. C. Azad, Md. Abul Kalam Fernandes, Edite Manuela da G. P. |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Espírito Santo, I. A. C. P. Costa, Lino Rocha, Ana Maria A. C. Azad, Md. Abul Kalam Fernandes, Edite Manuela da G. P. |
dc.subject.por.fl_str_mv |
Ciências Naturais::Ciências da Computação e da Informação |
topic |
Ciências Naturais::Ciências da Computação e da Informação |
description |
This chapter aims to address the challenging and demanding issue of solving a continuous nonlinear constrained global optimization problem. We propose four stochastic methods that rely on a population of points to diversify the search for a global solution: genetic algorithm, differential evolution, artificial fish swarm algorithm and electromagnetism-like mechanism. The performance of different variants of these algorithms is analyzed using a benchmark set of problems. Three different strategies to handle the equality and inequality constraints of the problem are addressed. An augmented Lagrangian-based technique, the tournament selection based on feasibility and dominance rules, and a strategy based on ranking objective and constraint violation are presented and tested. Numerical experiments are reported showing the effectiveness of our suggestions. Two well-known engineering design problems are successfully solved by the proposed methods. © Springer-Verlag Berlin Heidelberg 2013. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-10-18 2013-10-18T00:00:00Z |
dc.type.driver.fl_str_mv |
book part |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/50105 |
url |
http://hdl.handle.net/1822/50105 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Santo, I. A. E., Costa, L., Rocha, A. M. A., Azad, M. A. K., & Fernandes, E. M. (2013). On challenging techniques for constrained global optimization. In Handbook of Optimization (pp. 641-671). Springer, Berlin, Heidelberg 978-3-642-30503-0 1868-4394 10.1007/978-3-642-30504-7_26 978-3-642-30504-7 https://link.springer.com/chapter/10.1007/978-3-642-30504-7_26 |
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 |
Springer Verlag |
publisher.none.fl_str_mv |
Springer Verlag |
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 |
mluisa.alvim@gmail.com |
_version_ |
1817544584195997696 |