Adaptive improved flower pollination algorithm for global optimization
Autor(a) principal: | |
---|---|
Data de Publicação: | 2020 |
Outros Autores: | , , |
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. |
id |
UNSP_08483a5c3ced30cbb5df1b047a86ddc0 |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/232905 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
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:29462024-08-05T22:08:05.852940Repositório 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_ |
1808129395933577216 |