Globally optimal triangulations of minimum weight using Ant Colony Optimization metaheuristic

Autores
Dorzán, María Gisela; Gagliardi, Edilma Olinda; Leguizamón, Mario Guillermo; Hernández Peñalver, Gregorio
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Globally optimal triangulations are difficult to be found by deterministic methods as, for most type of criteria, no polynomial algorithm is known. In this work, we consider the Minimum Weight Triangulation (MWT) problem of a given set of n points in the plane. Our aim is to show how the Ant Colony Optimization (ACO) metaheuristic can be used to search for globally optimal triangulations of minimum weight. We present an experimental study for a set of instances for MWT problem. We create these instances since no reference to benchmarks for this problem were found in the literature. We assess through the experimental evaluation the applicability of the ACO metaheuristic for MWT problem.
Facultad de Informática
Materia
Ciencias Informáticas
Computational Geometry and Object Modeling
Heuristic methods
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/9668
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/9668
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Globally optimal triangulations of minimum weight using Ant Colony Optimization metaheuristicDorzán, María GiselaGagliardi, Edilma OlindaLeguizamón, Mario GuillermoHernández Peñalver, GregorioCiencias InformáticasComputational Geometry and Object ModelingHeuristic methodsGlobally optimal triangulations are difficult to be found by deterministic methods as, for most type of criteria, no polynomial algorithm is known. In this work, we consider the Minimum Weight Triangulation (MWT) problem of a given set of n points in the plane. Our aim is to show how the Ant Colony Optimization (ACO) metaheuristic can be used to search for globally optimal triangulations of minimum weight. We present an experimental study for a set of instances for MWT problem. We create these instances since no reference to benchmarks for this problem were found in the literature. We assess through the experimental evaluation the applicability of the ACO metaheuristic for MWT problem.Facultad de Informática2010-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf47-53http://sedici.unlp.edu.ar/handle/10915/9668enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Jun10-1.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/3.0/Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T10:43:21Zoai:sedici.unlp.edu.ar:10915/9668Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 10:43:21.841SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Globally optimal triangulations of minimum weight using Ant Colony Optimization metaheuristic
title Globally optimal triangulations of minimum weight using Ant Colony Optimization metaheuristic
spellingShingle Globally optimal triangulations of minimum weight using Ant Colony Optimization metaheuristic
Dorzán, María Gisela
Ciencias Informáticas
Computational Geometry and Object Modeling
Heuristic methods
title_short Globally optimal triangulations of minimum weight using Ant Colony Optimization metaheuristic
title_full Globally optimal triangulations of minimum weight using Ant Colony Optimization metaheuristic
title_fullStr Globally optimal triangulations of minimum weight using Ant Colony Optimization metaheuristic
title_full_unstemmed Globally optimal triangulations of minimum weight using Ant Colony Optimization metaheuristic
title_sort Globally optimal triangulations of minimum weight using Ant Colony Optimization metaheuristic
dc.creator.none.fl_str_mv Dorzán, María Gisela
Gagliardi, Edilma Olinda
Leguizamón, Mario Guillermo
Hernández Peñalver, Gregorio
author Dorzán, María Gisela
author_facet Dorzán, María Gisela
Gagliardi, Edilma Olinda
Leguizamón, Mario Guillermo
Hernández Peñalver, Gregorio
author_role author
author2 Gagliardi, Edilma Olinda
Leguizamón, Mario Guillermo
Hernández Peñalver, Gregorio
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Computational Geometry and Object Modeling
Heuristic methods
topic Ciencias Informáticas
Computational Geometry and Object Modeling
Heuristic methods
dc.description.none.fl_txt_mv Globally optimal triangulations are difficult to be found by deterministic methods as, for most type of criteria, no polynomial algorithm is known. In this work, we consider the Minimum Weight Triangulation (MWT) problem of a given set of n points in the plane. Our aim is to show how the Ant Colony Optimization (ACO) metaheuristic can be used to search for globally optimal triangulations of minimum weight. We present an experimental study for a set of instances for MWT problem. We create these instances since no reference to benchmarks for this problem were found in the literature. We assess through the experimental evaluation the applicability of the ACO metaheuristic for MWT problem.
Facultad de Informática
description Globally optimal triangulations are difficult to be found by deterministic methods as, for most type of criteria, no polynomial algorithm is known. In this work, we consider the Minimum Weight Triangulation (MWT) problem of a given set of n points in the plane. Our aim is to show how the Ant Colony Optimization (ACO) metaheuristic can be used to search for globally optimal triangulations of minimum weight. We present an experimental study for a set of instances for MWT problem. We create these instances since no reference to benchmarks for this problem were found in the literature. We assess through the experimental evaluation the applicability of the ACO metaheuristic for MWT problem.
publishDate 2010
dc.date.none.fl_str_mv 2010-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/9668
url http://sedici.unlp.edu.ar/handle/10915/9668
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Jun10-1.pdf
info:eu-repo/semantics/altIdentifier/issn/1666-6038
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
dc.format.none.fl_str_mv application/pdf
47-53
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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