Incest prevention and multirecombination in evolutionary algorithms to deal with the flow shop scheduling problem

Autores
Bain, María Elena; Vilanova, Gabriela; Gallard, Raúl Hector
Año de publicación
2000
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Scheduling concerns the allocation of limited resources for tasks over time. It is a process of making decisions that has, as a goal, the optimization of one or more objectives. Frequently, the main objective to be minimized is the completion time of the last job to abandon the system, which is called makespan. In many production systems a number of operations must be done on every job and often these operations have to be done in the same order on all jobs. This scheduling approach is known as the Flow Shop Scheduling Problem (FSSP). The present paper discusses the new multi-recombinative method and shows the performance of enhanced evolutionary approaches under permutation representation combined with a successfull previous approach proposed by another researchers, the extended incest prevention (EIP), consist of maintaining information about ancestors within the chromosome and modifying the selection for reproduction in order to impede mating of in di viduals belonging to the same "family", for a predefined number of generations. Results of the methods proposed here are contrasted with those obtained under previous evolutionary approaches to the FSSP.
I Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
evolutionary algorithms
genetic diversity
premature convergence
incest prevention
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:10915/23454

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spelling Incest prevention and multirecombination in evolutionary algorithms to deal with the flow shop scheduling problemBain, María ElenaVilanova, GabrielaGallard, Raúl HectorCiencias Informáticasevolutionary algorithmsgenetic diversitypremature convergenceincest preventionScheduling concerns the allocation of limited resources for tasks over time. It is a process of making decisions that has, as a goal, the optimization of one or more objectives. Frequently, the main objective to be minimized is the completion time of the last job to abandon the system, which is called makespan. In many production systems a number of operations must be done on every job and often these operations have to be done in the same order on all jobs. This scheduling approach is known as the Flow Shop Scheduling Problem (FSSP). The present paper discusses the new multi-recombinative method and shows the performance of enhanced evolutionary approaches under permutation representation combined with a successfull previous approach proposed by another researchers, the extended incest prevention (EIP), consist of maintaining information about ancestors within the chromosome and modifying the selection for reproduction in order to impede mating of in di viduals belonging to the same "family", for a predefined number of generations. Results of the methods proposed here are contrasted with those obtained under previous evolutionary approaches to the FSSP.I Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI)2000-10info: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/10915/23454enginfo: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:UNLP2025-09-03T10:28:16Zoai:sedici.unlp.edu.ar:10915/23454Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:28:17.621SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Incest prevention and multirecombination in evolutionary algorithms to deal with the flow shop scheduling problem
title Incest prevention and multirecombination in evolutionary algorithms to deal with the flow shop scheduling problem
spellingShingle Incest prevention and multirecombination in evolutionary algorithms to deal with the flow shop scheduling problem
Bain, María Elena
Ciencias Informáticas
evolutionary algorithms
genetic diversity
premature convergence
incest prevention
title_short Incest prevention and multirecombination in evolutionary algorithms to deal with the flow shop scheduling problem
title_full Incest prevention and multirecombination in evolutionary algorithms to deal with the flow shop scheduling problem
title_fullStr Incest prevention and multirecombination in evolutionary algorithms to deal with the flow shop scheduling problem
title_full_unstemmed Incest prevention and multirecombination in evolutionary algorithms to deal with the flow shop scheduling problem
title_sort Incest prevention and multirecombination in evolutionary algorithms to deal with the flow shop scheduling problem
dc.creator.none.fl_str_mv Bain, María Elena
Vilanova, Gabriela
Gallard, Raúl Hector
author Bain, María Elena
author_facet Bain, María Elena
Vilanova, Gabriela
Gallard, Raúl Hector
author_role author
author2 Vilanova, Gabriela
Gallard, Raúl Hector
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
evolutionary algorithms
genetic diversity
premature convergence
incest prevention
topic Ciencias Informáticas
evolutionary algorithms
genetic diversity
premature convergence
incest prevention
dc.description.none.fl_txt_mv Scheduling concerns the allocation of limited resources for tasks over time. It is a process of making decisions that has, as a goal, the optimization of one or more objectives. Frequently, the main objective to be minimized is the completion time of the last job to abandon the system, which is called makespan. In many production systems a number of operations must be done on every job and often these operations have to be done in the same order on all jobs. This scheduling approach is known as the Flow Shop Scheduling Problem (FSSP). The present paper discusses the new multi-recombinative method and shows the performance of enhanced evolutionary approaches under permutation representation combined with a successfull previous approach proposed by another researchers, the extended incest prevention (EIP), consist of maintaining information about ancestors within the chromosome and modifying the selection for reproduction in order to impede mating of in di viduals belonging to the same "family", for a predefined number of generations. Results of the methods proposed here are contrasted with those obtained under previous evolutionary approaches to the FSSP.
I Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
description Scheduling concerns the allocation of limited resources for tasks over time. It is a process of making decisions that has, as a goal, the optimization of one or more objectives. Frequently, the main objective to be minimized is the completion time of the last job to abandon the system, which is called makespan. In many production systems a number of operations must be done on every job and often these operations have to be done in the same order on all jobs. This scheduling approach is known as the Flow Shop Scheduling Problem (FSSP). The present paper discusses the new multi-recombinative method and shows the performance of enhanced evolutionary approaches under permutation representation combined with a successfull previous approach proposed by another researchers, the extended incest prevention (EIP), consist of maintaining information about ancestors within the chromosome and modifying the selection for reproduction in order to impede mating of in di viduals belonging to the same "family", for a predefined number of generations. Results of the methods proposed here are contrasted with those obtained under previous evolutionary approaches to the FSSP.
publishDate 2000
dc.date.none.fl_str_mv 2000-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
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dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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