A parallel evolutionary algorithm applied to the minimum interference frequency assignment problem

Autores
Mora, Gerardo; Perfumo, Cristian; Rojas, Lucas; Nesmachnow, Sergio
Año de publicación
2006
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
This article presents the application of a Parallel Evolutionary Algorithm to solve the Minimum Interference Frequency Assignment Problem (MI-FAP). This is a capital problem in the mobile telecommunication field, which proposes to find an assignation of a set of frequencies to minimize the communication interference. MI-FAP is a NP-Complete optimization problem; so traditional exact algorithms are useless for solving real-life problem instances in reasonable execution times. This work proposes to use a metaheuristic approach to find good quality solutions for real-life MIFAP instances never faced before using Evolutionary Algorithms. Evaluation experiments performed on those real-life instances report promising numerical results for both serial and parallel models of the algorithm proposed. In addition, the parallel version shows high levels of computational efficiency, demonstrating a superlinear speedup behavior for the instances studied
VII Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
minimum interference
frequency assignment problem
Parallel algorithms
Cellular architecture (e.g., mobile)
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:10915/22625
Acceder
id SEDICI_52254f0604ab6423c60520962b7b5e13
oai_identifier_str oai:sedici.unlp.edu.ar:10915/22625
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling A parallel evolutionary algorithm applied to the minimum interference frequency assignment problemMora, GerardoPerfumo, CristianRojas, LucasNesmachnow, SergioCiencias Informáticasminimum interferencefrequency assignment problemParallel algorithmsCellular architecture (e.g., mobile)This article presents the application of a Parallel Evolutionary Algorithm to solve the Minimum Interference Frequency Assignment Problem (MI-FAP). This is a capital problem in the mobile telecommunication field, which proposes to find an assignation of a set of frequencies to minimize the communication interference. MI-FAP is a NP-Complete optimization problem; so traditional exact algorithms are useless for solving real-life problem instances in reasonable execution times. This work proposes to use a metaheuristic approach to find good quality solutions for real-life MIFAP instances never faced before using Evolutionary Algorithms. Evaluation experiments performed on those real-life instances report promising numerical results for both serial and parallel models of the algorithm proposed. In addition, the parallel version shows high levels of computational efficiency, demonstrating a superlinear speedup behavior for the instances studiedVII Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI)2006-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf1163-1174http://sedici.unlp.edu.ar/handle/10915/22625enginfo: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:UNLP2025-09-29T10:55:07Zoai:sedici.unlp.edu.ar:10915/22625Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:07.412SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A parallel evolutionary algorithm applied to the minimum interference frequency assignment problem
title A parallel evolutionary algorithm applied to the minimum interference frequency assignment problem
spellingShingle A parallel evolutionary algorithm applied to the minimum interference frequency assignment problem
Mora, Gerardo
Ciencias Informáticas
minimum interference
frequency assignment problem
Parallel algorithms
Cellular architecture (e.g., mobile)
title_short A parallel evolutionary algorithm applied to the minimum interference frequency assignment problem
title_full A parallel evolutionary algorithm applied to the minimum interference frequency assignment problem
title_fullStr A parallel evolutionary algorithm applied to the minimum interference frequency assignment problem
title_full_unstemmed A parallel evolutionary algorithm applied to the minimum interference frequency assignment problem
title_sort A parallel evolutionary algorithm applied to the minimum interference frequency assignment problem
dc.creator.none.fl_str_mv Mora, Gerardo
Perfumo, Cristian
Rojas, Lucas
Nesmachnow, Sergio
author Mora, Gerardo
author_facet Mora, Gerardo
Perfumo, Cristian
Rojas, Lucas
Nesmachnow, Sergio
author_role author
author2 Perfumo, Cristian
Rojas, Lucas
Nesmachnow, Sergio
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
minimum interference
frequency assignment problem
Parallel algorithms
Cellular architecture (e.g., mobile)
topic Ciencias Informáticas
minimum interference
frequency assignment problem
Parallel algorithms
Cellular architecture (e.g., mobile)
dc.description.none.fl_txt_mv This article presents the application of a Parallel Evolutionary Algorithm to solve the Minimum Interference Frequency Assignment Problem (MI-FAP). This is a capital problem in the mobile telecommunication field, which proposes to find an assignation of a set of frequencies to minimize the communication interference. MI-FAP is a NP-Complete optimization problem; so traditional exact algorithms are useless for solving real-life problem instances in reasonable execution times. This work proposes to use a metaheuristic approach to find good quality solutions for real-life MIFAP instances never faced before using Evolutionary Algorithms. Evaluation experiments performed on those real-life instances report promising numerical results for both serial and parallel models of the algorithm proposed. In addition, the parallel version shows high levels of computational efficiency, demonstrating a superlinear speedup behavior for the instances studied
VII Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
description This article presents the application of a Parallel Evolutionary Algorithm to solve the Minimum Interference Frequency Assignment Problem (MI-FAP). This is a capital problem in the mobile telecommunication field, which proposes to find an assignation of a set of frequencies to minimize the communication interference. MI-FAP is a NP-Complete optimization problem; so traditional exact algorithms are useless for solving real-life problem instances in reasonable execution times. This work proposes to use a metaheuristic approach to find good quality solutions for real-life MIFAP instances never faced before using Evolutionary Algorithms. Evaluation experiments performed on those real-life instances report promising numerical results for both serial and parallel models of the algorithm proposed. In addition, the parallel version shows high levels of computational efficiency, demonstrating a superlinear speedup behavior for the instances studied
publishDate 2006
dc.date.none.fl_str_mv 2006-10
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/10915/22625
url http://sedici.unlp.edu.ar/handle/10915/22625
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
1163-1174
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_ 1844615809992753152
score 13.070432

Publicaciones similares