PhD. Subject: Strategies to design life-long learning heuristic based algorithms

Autores
Rojas Morales, Nicolás
Año de publicación
2014
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Nowadays combinatorial optimization problems arise in many circumstances, and we need to be able to solve these problems e ciently. Unfortunately, many of these problems are proven to be NP-hard, but problems can be related in some way. Analysing di erent combinatorial problems we can see some similarities between them. If we work with this similarities, we could improve the search process of an algorithm, because there exists some concurrent knowledge about solving a problem that could be exploited. For example, if an algorithm can solve an instance X for Sudoku puzzle ensuring uniqueness in blocks before rows and colums, this strategy can be useful for another instance Y when the algorithm is in a local optimum. In other words, some heuristics that can nd interesting candidate solutions can be reused in future during the execution of an algorithm. To do this, an algorithm should learn over time to determine how, when and which heuristic apply. The idea of this investigation is to create strategies to design life-long learning heuristic based algorithms. There have been some investigations in this area applied to 1-D Bin Packing problem, for Traveling Sales Problem and the most important thing, is that can be applied in different kinds of problem. (Párrafo extraído del texto a modo de resumen)
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
Materia
Ciencias Informáticas
Learning
Heuristic methods
Algorithms
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/41851

id SEDICI_1361b9a1009616b1fa39ebde043af457
oai_identifier_str oai:sedici.unlp.edu.ar:10915/41851
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling PhD. Subject: Strategies to design life-long learning heuristic based algorithmsRojas Morales, NicolásCiencias InformáticasLearningHeuristic methodsAlgorithmsNowadays combinatorial optimization problems arise in many circumstances, and we need to be able to solve these problems e ciently. Unfortunately, many of these problems are proven to be NP-hard, but problems can be related in some way. Analysing di erent combinatorial problems we can see some similarities between them. If we work with this similarities, we could improve the search process of an algorithm, because there exists some concurrent knowledge about solving a problem that could be exploited. For example, if an algorithm can solve an instance <i>X</i> for Sudoku puzzle ensuring uniqueness in blocks before rows and colums, this strategy can be useful for another instance Y when the algorithm is in a local optimum. In other words, some heuristics that can nd interesting candidate solutions can be reused in future during the execution of an algorithm. To do this, an algorithm should learn over time to determine how, when and which heuristic apply. The idea of this investigation is to create strategies to design life-long learning heuristic based algorithms. There have been some investigations in this area applied to 1-D Bin Packing problem, for Traveling Sales Problem and the most important thing, is that can be applied in different kinds of problem. <i>(Párrafo extraído del texto a modo de resumen)</i>Sociedad Argentina de Informática e Investigación Operativa (SADIO)2014-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf25-26http://sedici.unlp.edu.ar/handle/10915/41851enginfo:eu-repo/semantics/altIdentifier/url/http://43jaiio.sadio.org.ar/proceedings/IJCAI/25-26.pdfinfo:eu-repo/semantics/altIdentifier/issn/2362-5120info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/3.0/Creative Commons Attribution 3.0 Unported (CC BY 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:01:13Zoai:sedici.unlp.edu.ar:10915/41851Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:01:13.422SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv PhD. Subject: Strategies to design life-long learning heuristic based algorithms
title PhD. Subject: Strategies to design life-long learning heuristic based algorithms
spellingShingle PhD. Subject: Strategies to design life-long learning heuristic based algorithms
Rojas Morales, Nicolás
Ciencias Informáticas
Learning
Heuristic methods
Algorithms
title_short PhD. Subject: Strategies to design life-long learning heuristic based algorithms
title_full PhD. Subject: Strategies to design life-long learning heuristic based algorithms
title_fullStr PhD. Subject: Strategies to design life-long learning heuristic based algorithms
title_full_unstemmed PhD. Subject: Strategies to design life-long learning heuristic based algorithms
title_sort PhD. Subject: Strategies to design life-long learning heuristic based algorithms
dc.creator.none.fl_str_mv Rojas Morales, Nicolás
author Rojas Morales, Nicolás
author_facet Rojas Morales, Nicolás
author_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Learning
Heuristic methods
Algorithms
topic Ciencias Informáticas
Learning
Heuristic methods
Algorithms
dc.description.none.fl_txt_mv Nowadays combinatorial optimization problems arise in many circumstances, and we need to be able to solve these problems e ciently. Unfortunately, many of these problems are proven to be NP-hard, but problems can be related in some way. Analysing di erent combinatorial problems we can see some similarities between them. If we work with this similarities, we could improve the search process of an algorithm, because there exists some concurrent knowledge about solving a problem that could be exploited. For example, if an algorithm can solve an instance <i>X</i> for Sudoku puzzle ensuring uniqueness in blocks before rows and colums, this strategy can be useful for another instance Y when the algorithm is in a local optimum. In other words, some heuristics that can nd interesting candidate solutions can be reused in future during the execution of an algorithm. To do this, an algorithm should learn over time to determine how, when and which heuristic apply. The idea of this investigation is to create strategies to design life-long learning heuristic based algorithms. There have been some investigations in this area applied to 1-D Bin Packing problem, for Traveling Sales Problem and the most important thing, is that can be applied in different kinds of problem. <i>(Párrafo extraído del texto a modo de resumen)</i>
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
description Nowadays combinatorial optimization problems arise in many circumstances, and we need to be able to solve these problems e ciently. Unfortunately, many of these problems are proven to be NP-hard, but problems can be related in some way. Analysing di erent combinatorial problems we can see some similarities between them. If we work with this similarities, we could improve the search process of an algorithm, because there exists some concurrent knowledge about solving a problem that could be exploited. For example, if an algorithm can solve an instance <i>X</i> for Sudoku puzzle ensuring uniqueness in blocks before rows and colums, this strategy can be useful for another instance Y when the algorithm is in a local optimum. In other words, some heuristics that can nd interesting candidate solutions can be reused in future during the execution of an algorithm. To do this, an algorithm should learn over time to determine how, when and which heuristic apply. The idea of this investigation is to create strategies to design life-long learning heuristic based algorithms. There have been some investigations in this area applied to 1-D Bin Packing problem, for Traveling Sales Problem and the most important thing, is that can be applied in different kinds of problem. <i>(Párrafo extraído del texto a modo de resumen)</i>
publishDate 2014
dc.date.none.fl_str_mv 2014-09
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/10915/41851
url http://sedici.unlp.edu.ar/handle/10915/41851
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://43jaiio.sadio.org.ar/proceedings/IJCAI/25-26.pdf
info:eu-repo/semantics/altIdentifier/issn/2362-5120
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/3.0/
Creative Commons Attribution 3.0 Unported (CC BY 3.0)
dc.format.none.fl_str_mv application/pdf
25-26
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
_version_ 1844615878355714048
score 13.070432