A distance between populations for one-point crossover in genetic algorithms
Autor(a) principal: | |
---|---|
Data de Publicação: | 2012 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/118694 |
Resumo: | Manzoni, L., Vanneschi, L., & Mauri, G. (2012). A distance between populations for one-point crossover in genetic algorithms. Theoretical Computer Science, 429, 213-221. https://doi.org/10.1016/j.tcs.2011.12.041 |
id |
RCAP_cd5ce6346b90a5dfcf7a659ddbd4c8f9 |
---|---|
oai_identifier_str |
oai:run.unl.pt:10362/118694 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
A distance between populations for one-point crossover in genetic algorithmsTheoretical Computer ScienceComputer Science(all)Manzoni, L., Vanneschi, L., & Mauri, G. (2012). A distance between populations for one-point crossover in genetic algorithms. Theoretical Computer Science, 429, 213-221. https://doi.org/10.1016/j.tcs.2011.12.041Genetic algorithms use transformation operators on the genotypic structures of the individuals to carry out a search. These operators define a neighborhood. To analyze various dynamics of the search process, it is often useful to define a distance in this space. In fact, using an operator-based distance can make the analysis more accurate and reliable than using distances which have no relationship with the genetic operators. In this paper we define a distance which is based on the standard one-point crossover. Given that the population strongly affects the neighborhood induced by the crossover, we first define a crossover-based distance between populations. Successively, we show that it is naturally possible to derive from this function a family of distances between individuals. Finally, we also introduce an algorithm to compute this distance efficiently.NOVA Information Management School (NOVA IMS)RUNManzoni, LucaVanneschi, LeonardoMauri, Giancarlo2021-06-02T00:38:22Z2012-04-202012-04-20T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article9application/pdfhttp://hdl.handle.net/10362/118694eng0304-3975PURE: 31628166https://doi.org/10.1016/j.tcs.2011.12.041info: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:RCAAP2024-03-11T05:01:31Zoai:run.unl.pt:10362/118694Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:43:56.359815Repositório 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 |
A distance between populations for one-point crossover in genetic algorithms |
title |
A distance between populations for one-point crossover in genetic algorithms |
spellingShingle |
A distance between populations for one-point crossover in genetic algorithms Manzoni, Luca Theoretical Computer Science Computer Science(all) |
title_short |
A distance between populations for one-point crossover in genetic algorithms |
title_full |
A distance between populations for one-point crossover in genetic algorithms |
title_fullStr |
A distance between populations for one-point crossover in genetic algorithms |
title_full_unstemmed |
A distance between populations for one-point crossover in genetic algorithms |
title_sort |
A distance between populations for one-point crossover in genetic algorithms |
author |
Manzoni, Luca |
author_facet |
Manzoni, Luca Vanneschi, Leonardo Mauri, Giancarlo |
author_role |
author |
author2 |
Vanneschi, Leonardo Mauri, Giancarlo |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
NOVA Information Management School (NOVA IMS) RUN |
dc.contributor.author.fl_str_mv |
Manzoni, Luca Vanneschi, Leonardo Mauri, Giancarlo |
dc.subject.por.fl_str_mv |
Theoretical Computer Science Computer Science(all) |
topic |
Theoretical Computer Science Computer Science(all) |
description |
Manzoni, L., Vanneschi, L., & Mauri, G. (2012). A distance between populations for one-point crossover in genetic algorithms. Theoretical Computer Science, 429, 213-221. https://doi.org/10.1016/j.tcs.2011.12.041 |
publishDate |
2012 |
dc.date.none.fl_str_mv |
2012-04-20 2012-04-20T00:00:00Z 2021-06-02T00:38:22Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/118694 |
url |
http://hdl.handle.net/10362/118694 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0304-3975 PURE: 31628166 https://doi.org/10.1016/j.tcs.2011.12.041 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
9 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 |
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 |
|
_version_ |
1799138047911002112 |