Incorporating tabu search for local search into evolutionary algorithms to solve the job shop scheduling problem

A new issue for combinatorial optimization problems is to incorporate local search into the framework of evolutionary algorithms, leading to hybrid evolutionary algorithms. With the hybrid approach, evolutionary algorithms are used to perform global exploration among population while other heuristic...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Fernandez, Natalia, Salto, Carolina, Alfonso, Hugo, Gallard, Raúl Hector
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2001
Materias:
Ciencias Informáticas
Evolutionary algorithms
hybridization
local search
Scheduling
Optimization
Algorithms
ARTIFICIAL INTELLIGENCE
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/23409
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-23409
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
Evolutionary algorithms
hybridization
local search
Scheduling
Optimization
Algorithms
ARTIFICIAL INTELLIGENCE
spellingShingle Ciencias Informáticas
Evolutionary algorithms
hybridization
local search
Scheduling
Optimization
Algorithms
ARTIFICIAL INTELLIGENCE
Fernandez, Natalia
Salto, Carolina
Alfonso, Hugo
Gallard, Raúl Hector
Incorporating tabu search for local search into evolutionary algorithms to solve the job shop scheduling problem
topic_facet Ciencias Informáticas
Evolutionary algorithms
hybridization
local search
Scheduling
Optimization
Algorithms
ARTIFICIAL INTELLIGENCE
description A new issue for combinatorial optimization problems is to incorporate local search into the framework of evolutionary algorithms, leading to hybrid evolutionary algorithms. With the hybrid approach, evolutionary algorithms are used to perform global exploration among population while other heuristic methods are used to perform local exploitation around chromosomes. Due to the complementary properties of evolutionary algorithms and conventional heuristics, the hybrid approach often outperforms either method operating alone. When designing hybrid evolutionary algorithm (HEA), a fundamental principle is to hybridize where possible. This paper aims at developing powerful HEA to find high quality sub-optimal solutions for the job shop scheduling problem through tabu search (TS), an advanced local search meta-heuristic. Experiments of such a hybrid algorithm are carried out on different benchmark. Analysis of the behavior of the algorithm sheds light on ways to further improvement and are discussed here.
format Objeto de conferencia
Objeto de conferencia
author Fernandez, Natalia
Salto, Carolina
Alfonso, Hugo
Gallard, Raúl Hector
author_facet Fernandez, Natalia
Salto, Carolina
Alfonso, Hugo
Gallard, Raúl Hector
author_sort Fernandez, Natalia
title Incorporating tabu search for local search into evolutionary algorithms to solve the job shop scheduling problem
title_short Incorporating tabu search for local search into evolutionary algorithms to solve the job shop scheduling problem
title_full Incorporating tabu search for local search into evolutionary algorithms to solve the job shop scheduling problem
title_fullStr Incorporating tabu search for local search into evolutionary algorithms to solve the job shop scheduling problem
title_full_unstemmed Incorporating tabu search for local search into evolutionary algorithms to solve the job shop scheduling problem
title_sort incorporating tabu search for local search into evolutionary algorithms to solve the job shop scheduling problem
publishDate 2001
url http://sedici.unlp.edu.ar/handle/10915/23409
work_keys_str_mv AT fernandeznatalia incorporatingtabusearchforlocalsearchintoevolutionaryalgorithmstosolvethejobshopschedulingproblem
AT saltocarolina incorporatingtabusearchforlocalsearchintoevolutionaryalgorithmstosolvethejobshopschedulingproblem
AT alfonsohugo incorporatingtabusearchforlocalsearchintoevolutionaryalgorithmstosolvethejobshopschedulingproblem
AT gallardraulhector incorporatingtabusearchforlocalsearchintoevolutionaryalgorithmstosolvethejobshopschedulingproblem
bdutipo_str Repositorios
_version_ 1764820465889574915

Ejemplares similares