Incest prevention and multicore combinated evolutionary algorithms for the job shop scheduling problem

Evolutionary algorithms (EAs) have been successfully applied to scheduling problems. Current improvements towards convergence issues in EAs include incest prevention and multiplicity features. A multiplicity feature allows multiple recombination on multiple parents [7, 8, 9, 10]. The method was suc...

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Detalles Bibliográficos
Autores principales: Salto, Carolina, Stark, Natalia, Hugo, Alfonso, Gallard, Raúl Hector
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2001
Materias:
Ciencias Informáticas
Incest prevention
multicore combinated evolutionary algorithms
job shop scheduling problem
Algorithms
Scheduling
ARTIFICIAL INTELLIGENCE
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/21663
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-21663
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Incest prevention
multicore combinated evolutionary algorithms
job shop scheduling problem
Algorithms
Scheduling
ARTIFICIAL INTELLIGENCE
spellingShingle Ciencias Informáticas
Incest prevention
multicore combinated evolutionary algorithms
job shop scheduling problem
Algorithms
Scheduling
ARTIFICIAL INTELLIGENCE
Salto, Carolina
Stark, Natalia
Hugo, Alfonso
Gallard, Raúl Hector
Incest prevention and multicore combinated evolutionary algorithms for the job shop scheduling problem
topic_facet Ciencias Informáticas
Incest prevention
multicore combinated evolutionary algorithms
job shop scheduling problem
Algorithms
Scheduling
ARTIFICIAL INTELLIGENCE
description Evolutionary algorithms (EAs) have been successfully applied to scheduling problems. Current improvements towards convergence issues in EAs include incest prevention and multiplicity features. A multiplicity feature allows multiple recombination on multiple parents [7, 8, 9, 10]. The method was successfully applied to multimodal optimization problems. As a consequence of this approach it was detected that all individuals of the final population are much more centred on the optimum. This is an important issue when the application requires provision of multiple alternative near-optimal solutions confronting system dynamics as in production planning
format Objeto de conferencia
Objeto de conferencia
author Salto, Carolina
Stark, Natalia
Hugo, Alfonso
Gallard, Raúl Hector
author_facet Salto, Carolina
Stark, Natalia
Hugo, Alfonso
Gallard, Raúl Hector
author_sort Salto, Carolina
title Incest prevention and multicore combinated evolutionary algorithms for the job shop scheduling problem
title_short Incest prevention and multicore combinated evolutionary algorithms for the job shop scheduling problem
title_full Incest prevention and multicore combinated evolutionary algorithms for the job shop scheduling problem
title_fullStr Incest prevention and multicore combinated evolutionary algorithms for the job shop scheduling problem
title_full_unstemmed Incest prevention and multicore combinated evolutionary algorithms for the job shop scheduling problem
title_sort incest prevention and multicore combinated evolutionary algorithms for the job shop scheduling problem
publishDate 2001
url http://sedici.unlp.edu.ar/handle/10915/21663
work_keys_str_mv AT saltocarolina incestpreventionandmulticorecombinatedevolutionaryalgorithmsforthejobshopschedulingproblem
AT starknatalia incestpreventionandmulticorecombinatedevolutionaryalgorithmsforthejobshopschedulingproblem
AT hugoalfonso incestpreventionandmulticorecombinatedevolutionaryalgorithmsforthejobshopschedulingproblem
AT gallardraulhector incestpreventionandmulticorecombinatedevolutionaryalgorithmsforthejobshopschedulingproblem
bdutipo_str Repositorios
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