Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions

Autores
Harita, Maria; Wong, Alvaro; Rexachs del Rosario, Dolores; Luque Fadón, Emilio
Año de publicación
2020
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The evaluation in terms of quality of the results obtained from the use of a heuristic method is necessary to, first, verify the obtained results since heuristic methods do not guarantee to reach the optimum because all the possibilities are not fully explored. Secondly, it becomes interesting to validate such method, thus granting a high-quality index. Through our proposal, starting on the analysis of the literature survey on many optimization test functions, we are proposing the evaluation of a heuristic method based on Montecarlo approaches in conjunction with K-means clustering. Besides this, we aim to evaluate the results obtained through the use of some complex optimization test functions. Also, we seek to add a defined quality index to the original heuristic method relying on the consequent improvement in the results. As a side-work, we would aim to validate the heuristic mentioned aboveand optimize the algorithm in terms of scalability and quality.
Instituto de Investigación en Informática
Instituto de Investigación en Informática
Materia
Ciencias Informáticas
Heuristic method
Montecarlo
K-means
Benchmark functions
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/104772
Acceder
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spelling Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functionsHarita, MariaWong, AlvaroRexachs del Rosario, DoloresLuque Fadón, EmilioCiencias InformáticasHeuristic methodMontecarloK-meansBenchmark functionsThe evaluation in terms of quality of the results obtained from the use of a heuristic method is necessary to, first, verify the obtained results since heuristic methods do not guarantee to reach the optimum because all the possibilities are not fully explored. Secondly, it becomes interesting to validate such method, thus granting a high-quality index. Through our proposal, starting on the analysis of the literature survey on many optimization test functions, we are proposing the evaluation of a heuristic method based on Montecarlo approaches in conjunction with K-means clustering. Besides this, we aim to evaluate the results obtained through the use of some complex optimization test functions. Also, we seek to add a defined quality index to the original heuristic method relying on the consequent improvement in the results. As a side-work, we would aim to validate the heuristic mentioned aboveand optimize the algorithm in terms of scalability and quality.Instituto de Investigación en InformáticaInstituto de Investigación en Informática2020-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf36-39http://sedici.unlp.edu.ar/handle/10915/104772enginfo:eu-repo/semantics/altIdentifier/isbn/978-950-34-1927-4info:eu-repo/semantics/reference/hdl/10915/103585info:eu-repo/semantics/reference/hdl/10915/103585info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-11-12T10:47:16Zoai:sedici.unlp.edu.ar:10915/104772Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-11-12 10:47:16.511SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
title Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
spellingShingle Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
Harita, Maria
Ciencias Informáticas
Heuristic method
Montecarlo
K-means
Benchmark functions
title_short Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
title_full Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
title_fullStr Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
title_full_unstemmed Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
title_sort Evaluation of the quality of the ”Montecarlo plus K-means” heuristics using benchmark functions
dc.creator.none.fl_str_mv Harita, Maria
Wong, Alvaro
Rexachs del Rosario, Dolores
Luque Fadón, Emilio
author Harita, Maria
author_facet Harita, Maria
Wong, Alvaro
Rexachs del Rosario, Dolores
Luque Fadón, Emilio
author_role author
author2 Wong, Alvaro
Rexachs del Rosario, Dolores
Luque Fadón, Emilio
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Heuristic method
Montecarlo
K-means
Benchmark functions
topic Ciencias Informáticas
Heuristic method
Montecarlo
K-means
Benchmark functions
dc.description.none.fl_txt_mv The evaluation in terms of quality of the results obtained from the use of a heuristic method is necessary to, first, verify the obtained results since heuristic methods do not guarantee to reach the optimum because all the possibilities are not fully explored. Secondly, it becomes interesting to validate such method, thus granting a high-quality index. Through our proposal, starting on the analysis of the literature survey on many optimization test functions, we are proposing the evaluation of a heuristic method based on Montecarlo approaches in conjunction with K-means clustering. Besides this, we aim to evaluate the results obtained through the use of some complex optimization test functions. Also, we seek to add a defined quality index to the original heuristic method relying on the consequent improvement in the results. As a side-work, we would aim to validate the heuristic mentioned aboveand optimize the algorithm in terms of scalability and quality.
Instituto de Investigación en Informática
Instituto de Investigación en Informática
description The evaluation in terms of quality of the results obtained from the use of a heuristic method is necessary to, first, verify the obtained results since heuristic methods do not guarantee to reach the optimum because all the possibilities are not fully explored. Secondly, it becomes interesting to validate such method, thus granting a high-quality index. Through our proposal, starting on the analysis of the literature survey on many optimization test functions, we are proposing the evaluation of a heuristic method based on Montecarlo approaches in conjunction with K-means clustering. Besides this, we aim to evaluate the results obtained through the use of some complex optimization test functions. Also, we seek to add a defined quality index to the original heuristic method relying on the consequent improvement in the results. As a side-work, we would aim to validate the heuristic mentioned aboveand optimize the algorithm in terms of scalability and quality.
publishDate 2020
dc.date.none.fl_str_mv 2020-09
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/104772
url http://sedici.unlp.edu.ar/handle/10915/104772
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-950-34-1927-4
info:eu-repo/semantics/reference/hdl/10915/103585
info:eu-repo/semantics/reference/hdl/10915/103585
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
36-39
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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