Hybrid evolutionary algorithms to solve scheduling problems

The choice of a search algorithm can play a vital role in the success of a scheduling application. Evolutionary algorithms (EAs) can be used to solve this kind of combinatorial optimization problems. Compared to conventional heuristics (CH) and local search techniques (LS), EAs are not well suited f...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Minetti, Gabriela F., Salto, Carolina, Bermúdez, Carlos, Fernandez, Natalia, Alfonso, Hugo, Gallard, Raúl Hector
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2002
Materias:
Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Algorithms
Scheduling
Hybrid evolutionary algorithms
scheduling problems
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/22062
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-22062
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
ARTIFICIAL INTELLIGENCE
Algorithms
Scheduling
Hybrid evolutionary algorithms
scheduling problems
spellingShingle Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Algorithms
Scheduling
Hybrid evolutionary algorithms
scheduling problems
Minetti, Gabriela F.
Salto, Carolina
Bermúdez, Carlos
Fernandez, Natalia
Alfonso, Hugo
Gallard, Raúl Hector
Hybrid evolutionary algorithms to solve scheduling problems
topic_facet Ciencias Informáticas
ARTIFICIAL INTELLIGENCE
Algorithms
Scheduling
Hybrid evolutionary algorithms
scheduling problems
description The choice of a search algorithm can play a vital role in the success of a scheduling application. Evolutionary algorithms (EAs) can be used to solve this kind of combinatorial optimization problems. Compared to conventional heuristics (CH) and local search techniques (LS), EAs are not well suited for fine-tuninf those structures, which are very close to optimal solutions. Therefore, in complex problems, it is essential to build hybrid evolutionary algorithms (HEA) by incorporating CH and/or LS to provide fine-tuning. EAs are good at global search but slow to converge, while local search is good for fine-tuning but often falls into local optima. The hybrid approach complements the properties of evolutionary algorithm and other techniques. This research guide attempts to develop EAs hybridized with local search and conventional heuristics. They are incorporated at different stages of the evolutionary process. Either when the initial population is created, or in intermediate stages, or in the final population, or within the evolutionary process itself.
format Objeto de conferencia
Objeto de conferencia
author Minetti, Gabriela F.
Salto, Carolina
Bermúdez, Carlos
Fernandez, Natalia
Alfonso, Hugo
Gallard, Raúl Hector
author_facet Minetti, Gabriela F.
Salto, Carolina
Bermúdez, Carlos
Fernandez, Natalia
Alfonso, Hugo
Gallard, Raúl Hector
author_sort Minetti, Gabriela F.
title Hybrid evolutionary algorithms to solve scheduling problems
title_short Hybrid evolutionary algorithms to solve scheduling problems
title_full Hybrid evolutionary algorithms to solve scheduling problems
title_fullStr Hybrid evolutionary algorithms to solve scheduling problems
title_full_unstemmed Hybrid evolutionary algorithms to solve scheduling problems
title_sort hybrid evolutionary algorithms to solve scheduling problems
publishDate 2002
url http://sedici.unlp.edu.ar/handle/10915/22062
work_keys_str_mv AT minettigabrielaf hybridevolutionaryalgorithmstosolveschedulingproblems
AT saltocarolina hybridevolutionaryalgorithmstosolveschedulingproblems
AT bermudezcarlos hybridevolutionaryalgorithmstosolveschedulingproblems
AT fernandeznatalia hybridevolutionaryalgorithmstosolveschedulingproblems
AT alfonsohugo hybridevolutionaryalgorithmstosolveschedulingproblems
AT gallardraulhector hybridevolutionaryalgorithmstosolveschedulingproblems
bdutipo_str Repositorios
_version_ 1764820465424007169

Ejemplares similares