Multiobjective evolutionary algorithms for job shop scheduling

A job shop can be seen as a multi-operation model where jobs follows fixed routes, but not necessarily the same for each job. Job Shop Scheduling (JSS) attempts to provide optimal schedules according to some criterion. Common variables to optimize are makespan, machine idleness, lateness and total w...

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Detalles Bibliográficos
Autores principales: Esquivel, Susana Cecilia, Gallard, Raúl Hector, Ferrero, Sergio W.
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2001
Materias:
Ciencias Informáticas
Algorithms
Scheduling
ARTIFICIAL INTELLIGENCE
Multiobjective evolutionary algorithms
job shop scheduling
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/21667
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-21667
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
Algorithms
Scheduling
ARTIFICIAL INTELLIGENCE
Multiobjective evolutionary algorithms
job shop scheduling
spellingShingle Ciencias Informáticas
Algorithms
Scheduling
ARTIFICIAL INTELLIGENCE
Multiobjective evolutionary algorithms
job shop scheduling
Esquivel, Susana Cecilia
Gallard, Raúl Hector
Ferrero, Sergio W.
Multiobjective evolutionary algorithms for job shop scheduling
topic_facet Ciencias Informáticas
Algorithms
Scheduling
ARTIFICIAL INTELLIGENCE
Multiobjective evolutionary algorithms
job shop scheduling
description A job shop can be seen as a multi-operation model where jobs follows fixed routes, but not necessarily the same for each job. Job Shop Scheduling (JSS) attempts to provide optimal schedules according to some criterion. Common variables to optimize are makespan, machine idleness, lateness and total weighted completion time. According to this variables different objectives can be devised. Multiobjective optimization, also known as vector-valued criteria or multicriteria optimization, have long been used in many application areas where a problem involves multiple objectives, often conflicting, to be met or optimized. Multistage evolution and cooperative population search (CPS), as extended evolutive models, can be applied to solve multicriteria optimization, either using a plain aggregative approach or seeking the Pareto Front. Multirecombination and Local Search were introduced in the CPS method in order to speed up and to improve the evolution.
format Objeto de conferencia
Objeto de conferencia
author Esquivel, Susana Cecilia
Gallard, Raúl Hector
Ferrero, Sergio W.
author_facet Esquivel, Susana Cecilia
Gallard, Raúl Hector
Ferrero, Sergio W.
author_sort Esquivel, Susana Cecilia
title Multiobjective evolutionary algorithms for job shop scheduling
title_short Multiobjective evolutionary algorithms for job shop scheduling
title_full Multiobjective evolutionary algorithms for job shop scheduling
title_fullStr Multiobjective evolutionary algorithms for job shop scheduling
title_full_unstemmed Multiobjective evolutionary algorithms for job shop scheduling
title_sort multiobjective evolutionary algorithms for job shop scheduling
publishDate 2001
url http://sedici.unlp.edu.ar/handle/10915/21667
work_keys_str_mv AT esquivelsusanacecilia multiobjectiveevolutionaryalgorithmsforjobshopscheduling
AT gallardraulhector multiobjectiveevolutionaryalgorithmsforjobshopscheduling
AT ferrerosergiow multiobjectiveevolutionaryalgorithmsforjobshopscheduling
bdutipo_str Repositorios
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