Multirecombination and different representation in evolutionary algorithms for the flow shop scheduling problem

The flow shop scheduling problem (FSSP) has held the attention of many researchers. In a simplest usual situation, a set of jobs must follow the same route to be executed on a set of machines (resources) and the main objective is to optimize some performance variable (makespan, tardiness, lateness,...

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Detalles Bibliográficos
Autores principales: Bain, María Elena, Pandolfi, Daniel, Vilanova, Gabriela, Gallard, Raúl Hector
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2000
Materias:
Ciencias Informáticas
Scheduling
evolutíonary algorithms
multiple crossovers
multiple parents
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/23455
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-23455
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
Scheduling
evolutíonary algorithms
multiple crossovers
multiple parents
spellingShingle Ciencias Informáticas
Scheduling
evolutíonary algorithms
multiple crossovers
multiple parents
Bain, María Elena
Pandolfi, Daniel
Vilanova, Gabriela
Gallard, Raúl Hector
Multirecombination and different representation in evolutionary algorithms for the flow shop scheduling problem
topic_facet Ciencias Informáticas
Scheduling
evolutíonary algorithms
multiple crossovers
multiple parents
description The flow shop scheduling problem (FSSP) has held the attention of many researchers. In a simplest usual situation, a set of jobs must follow the same route to be executed on a set of machines (resources) and the main objective is to optimize some performance variable (makespan, tardiness, lateness, etc.). In the case of the makespan, it have been proved that when the number of machines is greater than or equal to three, the problem is NP-hard. EC is an emergent research field, which provides new heuristics to problem optimization where traditional approaches make the problem computationally intractable, is continuously showing its own evolution and enhanced approaches included latest multi-recombinative methods involving multiple crossovers per couple (MCPC) and multiple crossovers on multiple parents (MCMP). The present paper discusses the new multi-recombinative methods and shows the improvement of performance of enhanced evolutionary approaches under permutation and decode representation. Results of the methods proposed for each chromosome representation are here contrasted and results are shown.
format Objeto de conferencia
Objeto de conferencia
author Bain, María Elena
Pandolfi, Daniel
Vilanova, Gabriela
Gallard, Raúl Hector
author_facet Bain, María Elena
Pandolfi, Daniel
Vilanova, Gabriela
Gallard, Raúl Hector
author_sort Bain, María Elena
title Multirecombination and different representation in evolutionary algorithms for the flow shop scheduling problem
title_short Multirecombination and different representation in evolutionary algorithms for the flow shop scheduling problem
title_full Multirecombination and different representation in evolutionary algorithms for the flow shop scheduling problem
title_fullStr Multirecombination and different representation in evolutionary algorithms for the flow shop scheduling problem
title_full_unstemmed Multirecombination and different representation in evolutionary algorithms for the flow shop scheduling problem
title_sort multirecombination and different representation in evolutionary algorithms for the flow shop scheduling problem
publishDate 2000
url http://sedici.unlp.edu.ar/handle/10915/23455
work_keys_str_mv AT bainmariaelena multirecombinationanddifferentrepresentationinevolutionaryalgorithmsfortheflowshopschedulingproblem
AT pandolfidaniel multirecombinationanddifferentrepresentationinevolutionaryalgorithmsfortheflowshopschedulingproblem
AT vilanovagabriela multirecombinationanddifferentrepresentationinevolutionaryalgorithmsfortheflowshopschedulingproblem
AT gallardraulhector multirecombinationanddifferentrepresentationinevolutionaryalgorithmsfortheflowshopschedulingproblem
bdutipo_str Repositorios
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