Adaptive improved flower pollination algorithm for global optimization

Detalhes bibliográficos
Autor(a) principal: Rodrigues, Douglas
Data de Publicação: 2020
Outros Autores: de Rosa, Gustavo Henrique [UNESP], Passos, Leandro Aparecido, Papa, João Paulo [UNESP]
Tipo de documento: Capítulo de livro
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/978-3-030-28553-1_1
http://hdl.handle.net/11449/232905
Resumo: In the last few years, meta-heuristic-driven optimization algorithms have been employed to solve several problems since they can provide simple and elegant solutions. In this work, we introduced an improved adaptive version of the Flower Pollination Algorithm, which can dynamically change its parameter setting throughout the convergence process, as well as it keeps track of the best solutions. The effectiveness of the proposed approach is compared against with Bat Algorithm and Particle Swarm Optimization, as well as the naïve version of the Flower Pollination Algorithm. The experimental results were carried out in nine benchmark functions available in literature and demonstrated to outperform the other techniques with faster convergence rate.
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spelling Adaptive improved flower pollination algorithm for global optimizationBenchmarking functionsFlower pollination algorithmMeta-heuristic algorithmsOptimizationIn the last few years, meta-heuristic-driven optimization algorithms have been employed to solve several problems since they can provide simple and elegant solutions. In this work, we introduced an improved adaptive version of the Flower Pollination Algorithm, which can dynamically change its parameter setting throughout the convergence process, as well as it keeps track of the best solutions. The effectiveness of the proposed approach is compared against with Bat Algorithm and Particle Swarm Optimization, as well as the naïve version of the Flower Pollination Algorithm. The experimental results were carried out in nine benchmark functions available in literature and demonstrated to outperform the other techniques with faster convergence rate.Department of Computing São Carlos Federal UniversityDepartment of Computing São Paulo State UniversityDepartment of Computing São Paulo State UniversitySão Carlos Federal UniversityUniversidade Estadual Paulista (UNESP)Rodrigues, Douglasde Rosa, Gustavo Henrique [UNESP]Passos, Leandro AparecidoPapa, João Paulo [UNESP]2022-04-30T19:17:27Z2022-04-30T19:17:27Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookPart1-21http://dx.doi.org/10.1007/978-3-030-28553-1_1Studies in Computational Intelligence, v. 855, p. 1-21.1860-95031860-949Xhttp://hdl.handle.net/11449/23290510.1007/978-3-030-28553-1_12-s2.0-85072069070Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengStudies in Computational Intelligenceinfo:eu-repo/semantics/openAccess2024-04-23T16:11:01Zoai:repositorio.unesp.br:11449/232905Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-04-23T16:11:01Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Adaptive improved flower pollination algorithm for global optimization
title Adaptive improved flower pollination algorithm for global optimization
spellingShingle Adaptive improved flower pollination algorithm for global optimization
Rodrigues, Douglas
Benchmarking functions
Flower pollination algorithm
Meta-heuristic algorithms
Optimization
title_short Adaptive improved flower pollination algorithm for global optimization
title_full Adaptive improved flower pollination algorithm for global optimization
title_fullStr Adaptive improved flower pollination algorithm for global optimization
title_full_unstemmed Adaptive improved flower pollination algorithm for global optimization
title_sort Adaptive improved flower pollination algorithm for global optimization
author Rodrigues, Douglas
author_facet Rodrigues, Douglas
de Rosa, Gustavo Henrique [UNESP]
Passos, Leandro Aparecido
Papa, João Paulo [UNESP]
author_role author
author2 de Rosa, Gustavo Henrique [UNESP]
Passos, Leandro Aparecido
Papa, João Paulo [UNESP]
author2_role author
author
author
dc.contributor.none.fl_str_mv São Carlos Federal University
Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Rodrigues, Douglas
de Rosa, Gustavo Henrique [UNESP]
Passos, Leandro Aparecido
Papa, João Paulo [UNESP]
dc.subject.por.fl_str_mv Benchmarking functions
Flower pollination algorithm
Meta-heuristic algorithms
Optimization
topic Benchmarking functions
Flower pollination algorithm
Meta-heuristic algorithms
Optimization
description In the last few years, meta-heuristic-driven optimization algorithms have been employed to solve several problems since they can provide simple and elegant solutions. In this work, we introduced an improved adaptive version of the Flower Pollination Algorithm, which can dynamically change its parameter setting throughout the convergence process, as well as it keeps track of the best solutions. The effectiveness of the proposed approach is compared against with Bat Algorithm and Particle Swarm Optimization, as well as the naïve version of the Flower Pollination Algorithm. The experimental results were carried out in nine benchmark functions available in literature and demonstrated to outperform the other techniques with faster convergence rate.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
2022-04-30T19:17:27Z
2022-04-30T19:17:27Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/bookPart
format bookPart
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1007/978-3-030-28553-1_1
Studies in Computational Intelligence, v. 855, p. 1-21.
1860-9503
1860-949X
http://hdl.handle.net/11449/232905
10.1007/978-3-030-28553-1_1
2-s2.0-85072069070
url http://dx.doi.org/10.1007/978-3-030-28553-1_1
http://hdl.handle.net/11449/232905
identifier_str_mv Studies in Computational Intelligence, v. 855, p. 1-21.
1860-9503
1860-949X
10.1007/978-3-030-28553-1_1
2-s2.0-85072069070
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Studies in Computational Intelligence
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1-21
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1799965516820905984

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