Non-geometric pulse: An adaptive geometricity approach for Genetic Algorithms
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/145483 |
Resumo: | Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science |
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7160 |
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Non-geometric pulse: An adaptive geometricity approach for Genetic AlgorithmsConvex SearchEvolutionary AlgorithmsGenetic AlgorithmsGeometric semantic operatorsDiversity maintenanceDissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceEvolutionary algorithms (EAs) are a family of algorithms inspired by the Darwinian theory of evolution. Mathematics, particularly geometry and topology, allows for the possibility of developing a general geometrical framework and consequently generating deeper insights that may be shared among the different EAs. Genetic Algorithm (GA), inspired by Darwin’s theory of natural selection, is a popular algorithm among EAs. This is a population-based, fitness-oriented algorithm that performs a convex heuristic search to optimize a plethora of problems. Common limitations of GA as well as other EAs have geometrical origins like premature convergence, where the final population’s convex-hull might not include the best solution, called Global Optima. Population diversity maintenance is a key idea that tries to tackle this problem but is often performed through geometrical methods that constantly diminish the search space’s area. In this work, a self-adaptive geometricity approach will be presented. In particular, the non-geometric crossover is strategically employed in a symbiotic relation with geometric crossover, maintaining diversity in a logical way from a geometric/topological grammar standpoint. A comparison with well-known diversity maintenance methods is provided, using common benchmarks that serve as general testing ground for the considered techniques.Castelli, MauroManzoni, LucaRUNFerreira, José Pedro Mendes Ribeiro do Vale2023-10-24T00:31:26Z2022-10-242022-10-24T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/145483TID:203105702enginfo: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:RCAAP2024-03-11T05:25:54Zoai:run.unl.pt:10362/145483Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:52:06.206048Repositório 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 |
Non-geometric pulse: An adaptive geometricity approach for Genetic Algorithms |
title |
Non-geometric pulse: An adaptive geometricity approach for Genetic Algorithms |
spellingShingle |
Non-geometric pulse: An adaptive geometricity approach for Genetic Algorithms Ferreira, José Pedro Mendes Ribeiro do Vale Convex Search Evolutionary Algorithms Genetic Algorithms Geometric semantic operators Diversity maintenance |
title_short |
Non-geometric pulse: An adaptive geometricity approach for Genetic Algorithms |
title_full |
Non-geometric pulse: An adaptive geometricity approach for Genetic Algorithms |
title_fullStr |
Non-geometric pulse: An adaptive geometricity approach for Genetic Algorithms |
title_full_unstemmed |
Non-geometric pulse: An adaptive geometricity approach for Genetic Algorithms |
title_sort |
Non-geometric pulse: An adaptive geometricity approach for Genetic Algorithms |
author |
Ferreira, José Pedro Mendes Ribeiro do Vale |
author_facet |
Ferreira, José Pedro Mendes Ribeiro do Vale |
author_role |
author |
dc.contributor.none.fl_str_mv |
Castelli, Mauro Manzoni, Luca RUN |
dc.contributor.author.fl_str_mv |
Ferreira, José Pedro Mendes Ribeiro do Vale |
dc.subject.por.fl_str_mv |
Convex Search Evolutionary Algorithms Genetic Algorithms Geometric semantic operators Diversity maintenance |
topic |
Convex Search Evolutionary Algorithms Genetic Algorithms Geometric semantic operators Diversity maintenance |
description |
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data Science |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-10-24 2022-10-24T00:00:00Z 2023-10-24T00:31:26Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/145483 TID:203105702 |
url |
http://hdl.handle.net/10362/145483 |
identifier_str_mv |
TID:203105702 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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.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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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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 |
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1799138112925859840 |