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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/23454
Ver los metadatos del registro completo
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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 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/10915/23454 |
url |
http://sedici.unlp.edu.ar/handle/10915/23454 |
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) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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