On Challenging Techniques for Constrained Global Optimization

Detalhes bibliográficos
Autor(a) principal: Espírito Santo, I. A. C. P.
Data de Publicação: 2013
Outros Autores: Costa, Lino, Rocha, Ana Maria A. C., Azad, Md. Abul Kalam, Fernandes, Edite Manuela da G. P.
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.
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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
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