On the possibility to design evolutionary algorithms with optimal equilibrium distribution : The case of simulated annealing

Autores
Segura, Enrique Carlos
Año de publicación
2005
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In this paper a thermodynamic approach is presented to the problem of convergence of evolutionary algorithms. The case of the Simulated Annealing algorithm for optimisation is considered as a simple evolution strategy with a control parameter allowing balance between the probability of obtaining an optimal or near-optimal solution and the time that the algorithm will take to reach equilibrium. This capacity is analysed and a theoretical frame is presented, stating a general condition to be fulfilled by an evolutionary algorithm in order to ensure its convergence to a global maximum of the fitness function.
Eje: VI Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática
Materia
Ciencias Informáticas
Simulated annealing
evolutionary computation
thermodynamics of equilibrium
ergodicity
detailed balance
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/22922
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/22922
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling On the possibility to design evolutionary algorithms with optimal equilibrium distribution : The case of simulated annealingSegura, Enrique CarlosCiencias InformáticasSimulated annealingevolutionary computationthermodynamics of equilibriumergodicitydetailed balanceIn this paper a thermodynamic approach is presented to the problem of convergence of evolutionary algorithms. The case of the Simulated Annealing algorithm for optimisation is considered as a simple evolution strategy with a control parameter allowing balance between the probability of obtaining an optimal or near-optimal solution and the time that the algorithm will take to reach equilibrium. This capacity is analysed and a theoretical frame is presented, stating a general condition to be fulfilled by an evolutionary algorithm in order to ensure its convergence to a global maximum of the fitness function.Eje: VI Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática2005-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/22922enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-12-23T10:58:06Zoai:sedici.unlp.edu.ar:10915/22922Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-12-23 10:58:06.985SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv On the possibility to design evolutionary algorithms with optimal equilibrium distribution : The case of simulated annealing
title On the possibility to design evolutionary algorithms with optimal equilibrium distribution : The case of simulated annealing
spellingShingle On the possibility to design evolutionary algorithms with optimal equilibrium distribution : The case of simulated annealing
Segura, Enrique Carlos
Ciencias Informáticas
Simulated annealing
evolutionary computation
thermodynamics of equilibrium
ergodicity
detailed balance
title_short On the possibility to design evolutionary algorithms with optimal equilibrium distribution : The case of simulated annealing
title_full On the possibility to design evolutionary algorithms with optimal equilibrium distribution : The case of simulated annealing
title_fullStr On the possibility to design evolutionary algorithms with optimal equilibrium distribution : The case of simulated annealing
title_full_unstemmed On the possibility to design evolutionary algorithms with optimal equilibrium distribution : The case of simulated annealing
title_sort On the possibility to design evolutionary algorithms with optimal equilibrium distribution : The case of simulated annealing
dc.creator.none.fl_str_mv Segura, Enrique Carlos
author Segura, Enrique Carlos
author_facet Segura, Enrique Carlos
author_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Simulated annealing
evolutionary computation
thermodynamics of equilibrium
ergodicity
detailed balance
topic Ciencias Informáticas
Simulated annealing
evolutionary computation
thermodynamics of equilibrium
ergodicity
detailed balance
dc.description.none.fl_txt_mv In this paper a thermodynamic approach is presented to the problem of convergence of evolutionary algorithms. The case of the Simulated Annealing algorithm for optimisation is considered as a simple evolution strategy with a control parameter allowing balance between the probability of obtaining an optimal or near-optimal solution and the time that the algorithm will take to reach equilibrium. This capacity is analysed and a theoretical frame is presented, stating a general condition to be fulfilled by an evolutionary algorithm in order to ensure its convergence to a global maximum of the fitness function.
Eje: VI Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática
description In this paper a thermodynamic approach is presented to the problem of convergence of evolutionary algorithms. The case of the Simulated Annealing algorithm for optimisation is considered as a simple evolution strategy with a control parameter allowing balance between the probability of obtaining an optimal or near-optimal solution and the time that the algorithm will take to reach equilibrium. This capacity is analysed and a theoretical frame is presented, stating a general condition to be fulfilled by an evolutionary algorithm in order to ensure its convergence to a global maximum of the fitness function.
publishDate 2005
dc.date.none.fl_str_mv 2005-10
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/10915/22922
url http://sedici.unlp.edu.ar/handle/10915/22922
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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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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