Energy-saving light positioning using heuristic search

A new definition is given to the problem of light positioning in a closed environment, aiming at obtaining, for a global illumination radiosity solution, the position and emission power for a given number of lights that provide a desired illumination at a minimum total emission power. Such a desired...

Descripción completa

Detalles Bibliográficos
Autores: Castro Villegas, Francesc, Acebo Peña, Esteve del, Sbert, Mateu
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2012
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/11676
Acceso en línea:http://hdl.handle.net/10256/11676
Access Level:acceso embargado
Palabra clave:Programació heurística
Heuristic programming
Intel·ligència artificial
Artificial intelligence
Algorismes genètics
Computer algorithms
id ES_c9251be71bef93d9f5885fbdccf06bc5
oai_identifier_str oai:recercat.cat:10256/11676
network_acronym_str ES
network_name_str España
repository_id_str
spelling Energy-saving light positioning using heuristic searchCastro Villegas, FrancescAcebo Peña, Esteve delSbert, MateuProgramació heurísticaHeuristic programmingIntel·ligència artificialArtificial intelligenceAlgorismes genèticsComputer algorithmsA new definition is given to the problem of light positioning in a closed environment, aiming at obtaining, for a global illumination radiosity solution, the position and emission power for a given number of lights that provide a desired illumination at a minimum total emission power. Such a desired illumination is expressed using minimum and/or maximum values of irradiance allowed, resulting in a combinatory optimization problem. A pre-process computes and stores irradiances for a pre-established set of light positions by means of a radiosity random walk. The reuse of photon paths makes this pre-process reasonably cheap. Different heuristic search algorithms, combined to linear programming, are discussed and compared, from the simplest hill climbing strategies to the more sophisticated population-based and hybrid approaches. The paper shows how the presented approaches make it possible to obtain a good solution to the problem at a reasonable costThis project has been funded in part with grant number TIN2010-21089-C03-01 from Spanish Government, and with grant number 2009 SGR 643 from Catalan GovernmentElsevierMinisterio de Ciencia e Innovación (Espanya)Generalitat de Catalunya. Agència de Gestió d'Ajuts Universitaris i de Recercainfoinfo2012info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10256/11676http://hdl.handle.net/10256/11676© Engineering Applications of Artificial Intelligence, 2012, vol. 25, núm.3, p. 566-582Articles publicats (D-IMA)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)Inglésinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.engappai.2011.11.009info:eu-repo/semantics/altIdentifier/issn/0952-1976info:eu-repo/semantics/altIdentifier/issn/0952-1976info:eu-repo/grantAgreement/MICINN//TIN2010-21089-C03-01AGAUR/2009-2014/2009 SGR-643Tots els drets reservatsinfo:eu-repo/semantics/embargoedAccessoai:recercat.cat:10256/116762026-05-29T05:05:01Z
dc.title.none.fl_str_mv Energy-saving light positioning using heuristic search
title Energy-saving light positioning using heuristic search
spellingShingle Energy-saving light positioning using heuristic search
Castro Villegas, Francesc
Programació heurística
Heuristic programming
Intel·ligència artificial
Artificial intelligence
Algorismes genètics
Computer algorithms
title_short Energy-saving light positioning using heuristic search
title_full Energy-saving light positioning using heuristic search
title_fullStr Energy-saving light positioning using heuristic search
title_full_unstemmed Energy-saving light positioning using heuristic search
title_sort Energy-saving light positioning using heuristic search
dc.creator.none.fl_str_mv Castro Villegas, Francesc
Acebo Peña, Esteve del
Sbert, Mateu
author Castro Villegas, Francesc
author_facet Castro Villegas, Francesc
Acebo Peña, Esteve del
Sbert, Mateu
author_role author
author2 Acebo Peña, Esteve del
Sbert, Mateu
author2_role author
author
dc.contributor.none.fl_str_mv Ministerio de Ciencia e Innovación (Espanya)
Generalitat de Catalunya. Agència de Gestió d'Ajuts Universitaris i de Recerca
dc.subject.none.fl_str_mv Programació heurística
Heuristic programming
Intel·ligència artificial
Artificial intelligence
Algorismes genètics
Computer algorithms
topic Programació heurística
Heuristic programming
Intel·ligència artificial
Artificial intelligence
Algorismes genètics
Computer algorithms
description A new definition is given to the problem of light positioning in a closed environment, aiming at obtaining, for a global illumination radiosity solution, the position and emission power for a given number of lights that provide a desired illumination at a minimum total emission power. Such a desired illumination is expressed using minimum and/or maximum values of irradiance allowed, resulting in a combinatory optimization problem. A pre-process computes and stores irradiances for a pre-established set of light positions by means of a radiosity random walk. The reuse of photon paths makes this pre-process reasonably cheap. Different heuristic search algorithms, combined to linear programming, are discussed and compared, from the simplest hill climbing strategies to the more sophisticated population-based and hybrid approaches. The paper shows how the presented approaches make it possible to obtain a good solution to the problem at a reasonable cost
publishDate 2012
dc.date.none.fl_str_mv 2012
info
info
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10256/11676
http://hdl.handle.net/10256/11676
url http://hdl.handle.net/10256/11676
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.engappai.2011.11.009
info:eu-repo/semantics/altIdentifier/issn/0952-1976
info:eu-repo/semantics/altIdentifier/issn/0952-1976
info:eu-repo/grantAgreement/MICINN//TIN2010-21089-C03-01
AGAUR/2009-2014/2009 SGR-643
dc.rights.none.fl_str_mv Tots els drets reservats
info:eu-repo/semantics/embargoedAccess
rights_invalid_str_mv Tots els drets reservats
eu_rights_str_mv embargoedAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv © Engineering Applications of Artificial Intelligence, 2012, vol. 25, núm.3, p. 566-582
Articles publicats (D-IMA)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869419346340610049
score 15,811543

Similares en LA Referencia