Greedy Seeding Procedure for GAs Solving a Strip Packing Problem

Autores
Salto, Carolina; Alba, Enrique; Molina, Juan M.; Leguizamon, Guillermo Nolasco
Año de publicación
2008
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this paper, the two-dimensional strip packing problem with 3-stage level patterns is tackled using genetic algorithms (GAs). We evaluate the usefulness of a knowledge-based greedy seeding procedure used for creating the initial population. This is motivated by the expectation that the seeding will speed up the GA by starting the search in promising regions of the search space. An analysis of the impact of the seeded initial population is offered, together with a complete study of the influence of these modifications on the genetic search. The results show that the use of an appropriate seeding of the initial population outperforms existing GA approaches on all the used problem instances, for all the metrics used, and in fact it represents the new state of the art for this problem.
Fil: Salto, Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Pampa. Facultad de Ingeniería. Departamento de Informática; Argentina
Fil: Alba, Enrique. Universidad de Malaga. Escuela Técnica Superior de Ingeniería Informática.; España
Fil: Molina, Juan M.. Universidad de Malaga. Escuela Técnica Superior de Ingeniería Informática.; España
Fil: Leguizamon, Guillermo Nolasco. Universidad Nacional de San Luis; Argentina
Materia
GENETIC ALGORITHMS
STRIP PACKING
SEEDING
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/158396

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spelling Greedy Seeding Procedure for GAs Solving a Strip Packing ProblemSalto, CarolinaAlba, EnriqueMolina, Juan M.Leguizamon, Guillermo NolascoGENETIC ALGORITHMSSTRIP PACKINGSEEDINGhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1In this paper, the two-dimensional strip packing problem with 3-stage level patterns is tackled using genetic algorithms (GAs). We evaluate the usefulness of a knowledge-based greedy seeding procedure used for creating the initial population. This is motivated by the expectation that the seeding will speed up the GA by starting the search in promising regions of the search space. An analysis of the impact of the seeded initial population is offered, together with a complete study of the influence of these modifications on the genetic search. The results show that the use of an appropriate seeding of the initial population outperforms existing GA approaches on all the used problem instances, for all the metrics used, and in fact it represents the new state of the art for this problem.Fil: Salto, Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Pampa. Facultad de Ingeniería. Departamento de Informática; ArgentinaFil: Alba, Enrique. Universidad de Malaga. Escuela Técnica Superior de Ingeniería Informática.; EspañaFil: Molina, Juan M.. Universidad de Malaga. Escuela Técnica Superior de Ingeniería Informática.; EspañaFil: Leguizamon, Guillermo Nolasco. Universidad Nacional de San Luis; ArgentinaSociedad Iberoamericana de Inteligencia Artificial2008-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/158396Salto, Carolina; Alba, Enrique; Molina, Juan M.; Leguizamon, Guillermo Nolasco; Greedy Seeding Procedure for GAs Solving a Strip Packing Problem; Sociedad Iberoamericana de Inteligencia Artificial; Inteligencia Artificial; 12; 40; 12-2008; 73-851137-36011988-3064CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://journal.iberamia.org/public/Vol.1-14.htmlinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:17:40Zoai:ri.conicet.gov.ar:11336/158396instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 15:17:40.358CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Greedy Seeding Procedure for GAs Solving a Strip Packing Problem
title Greedy Seeding Procedure for GAs Solving a Strip Packing Problem
spellingShingle Greedy Seeding Procedure for GAs Solving a Strip Packing Problem
Salto, Carolina
GENETIC ALGORITHMS
STRIP PACKING
SEEDING
title_short Greedy Seeding Procedure for GAs Solving a Strip Packing Problem
title_full Greedy Seeding Procedure for GAs Solving a Strip Packing Problem
title_fullStr Greedy Seeding Procedure for GAs Solving a Strip Packing Problem
title_full_unstemmed Greedy Seeding Procedure for GAs Solving a Strip Packing Problem
title_sort Greedy Seeding Procedure for GAs Solving a Strip Packing Problem
dc.creator.none.fl_str_mv Salto, Carolina
Alba, Enrique
Molina, Juan M.
Leguizamon, Guillermo Nolasco
author Salto, Carolina
author_facet Salto, Carolina
Alba, Enrique
Molina, Juan M.
Leguizamon, Guillermo Nolasco
author_role author
author2 Alba, Enrique
Molina, Juan M.
Leguizamon, Guillermo Nolasco
author2_role author
author
author
dc.subject.none.fl_str_mv GENETIC ALGORITHMS
STRIP PACKING
SEEDING
topic GENETIC ALGORITHMS
STRIP PACKING
SEEDING
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In this paper, the two-dimensional strip packing problem with 3-stage level patterns is tackled using genetic algorithms (GAs). We evaluate the usefulness of a knowledge-based greedy seeding procedure used for creating the initial population. This is motivated by the expectation that the seeding will speed up the GA by starting the search in promising regions of the search space. An analysis of the impact of the seeded initial population is offered, together with a complete study of the influence of these modifications on the genetic search. The results show that the use of an appropriate seeding of the initial population outperforms existing GA approaches on all the used problem instances, for all the metrics used, and in fact it represents the new state of the art for this problem.
Fil: Salto, Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de La Pampa. Facultad de Ingeniería. Departamento de Informática; Argentina
Fil: Alba, Enrique. Universidad de Malaga. Escuela Técnica Superior de Ingeniería Informática.; España
Fil: Molina, Juan M.. Universidad de Malaga. Escuela Técnica Superior de Ingeniería Informática.; España
Fil: Leguizamon, Guillermo Nolasco. Universidad Nacional de San Luis; Argentina
description In this paper, the two-dimensional strip packing problem with 3-stage level patterns is tackled using genetic algorithms (GAs). We evaluate the usefulness of a knowledge-based greedy seeding procedure used for creating the initial population. This is motivated by the expectation that the seeding will speed up the GA by starting the search in promising regions of the search space. An analysis of the impact of the seeded initial population is offered, together with a complete study of the influence of these modifications on the genetic search. The results show that the use of an appropriate seeding of the initial population outperforms existing GA approaches on all the used problem instances, for all the metrics used, and in fact it represents the new state of the art for this problem.
publishDate 2008
dc.date.none.fl_str_mv 2008-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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://hdl.handle.net/11336/158396
Salto, Carolina; Alba, Enrique; Molina, Juan M.; Leguizamon, Guillermo Nolasco; Greedy Seeding Procedure for GAs Solving a Strip Packing Problem; Sociedad Iberoamericana de Inteligencia Artificial; Inteligencia Artificial; 12; 40; 12-2008; 73-85
1137-3601
1988-3064
CONICET Digital
CONICET
url http://hdl.handle.net/11336/158396
identifier_str_mv Salto, Carolina; Alba, Enrique; Molina, Juan M.; Leguizamon, Guillermo Nolasco; Greedy Seeding Procedure for GAs Solving a Strip Packing Problem; Sociedad Iberoamericana de Inteligencia Artificial; Inteligencia Artificial; 12; 40; 12-2008; 73-85
1137-3601
1988-3064
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://journal.iberamia.org/public/Vol.1-14.html
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Sociedad Iberoamericana de Inteligencia Artificial
publisher.none.fl_str_mv Sociedad Iberoamericana de Inteligencia Artificial
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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