Different evolutionary approaches to solve the flow shop scheduling problem

Over the past three decades extensive search have been done on pure m-machine flow shop problems. Many researchers faced the Flow Shop Scheduling Problem (FSSP) by means of well-known heuristics which, are successfully used for certain instances of the problem providing a single acceptable solution...

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Detalles Bibliográficos
Autores principales: Esquivel, Susana Cecilia, Gallard, Raúl Hector, Zuppa, Federico
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2001
Materias:
Ciencias Informáticas
Different evolutionary approaches
ARTIFICIAL INTELLIGENCE
Scheduling
flow shop scheduling problem
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/21654
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-21654
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
Different evolutionary approaches
ARTIFICIAL INTELLIGENCE
Scheduling
flow shop scheduling problem
spellingShingle Ciencias Informáticas
Different evolutionary approaches
ARTIFICIAL INTELLIGENCE
Scheduling
flow shop scheduling problem
Esquivel, Susana Cecilia
Gallard, Raúl Hector
Zuppa, Federico
Different evolutionary approaches to solve the flow shop scheduling problem
topic_facet Ciencias Informáticas
Different evolutionary approaches
ARTIFICIAL INTELLIGENCE
Scheduling
flow shop scheduling problem
description Over the past three decades extensive search have been done on pure m-machine flow shop problems. Many researchers faced the Flow Shop Scheduling Problem (FSSP) by means of well-known heuristics which, are successfully used for certain instances of the problem providing a single acceptable solution. Current trends involve distinct evolutionary computation approaches. This work shows [5, 6, 7] implementations of diverse evolutionary approaches on a set of flow shop scheduling instances, including latest approaches using a multirecombination feature, Multiple Crossovers per Couple (MCPC), and partial replacement of the population when possible stagnation is detected. A discussion on implementation details, analysis and a comparison of evolutionary and conventional approaches to the problem are shown.
format Objeto de conferencia
Objeto de conferencia
author Esquivel, Susana Cecilia
Gallard, Raúl Hector
Zuppa, Federico
author_facet Esquivel, Susana Cecilia
Gallard, Raúl Hector
Zuppa, Federico
author_sort Esquivel, Susana Cecilia
title Different evolutionary approaches to solve the flow shop scheduling problem
title_short Different evolutionary approaches to solve the flow shop scheduling problem
title_full Different evolutionary approaches to solve the flow shop scheduling problem
title_fullStr Different evolutionary approaches to solve the flow shop scheduling problem
title_full_unstemmed Different evolutionary approaches to solve the flow shop scheduling problem
title_sort different evolutionary approaches to solve the flow shop scheduling problem
publishDate 2001
url http://sedici.unlp.edu.ar/handle/10915/21654
work_keys_str_mv AT esquivelsusanacecilia differentevolutionaryapproachestosolvetheflowshopschedulingproblem
AT gallardraulhector differentevolutionaryapproachestosolvetheflowshopschedulingproblem
AT zuppafederico differentevolutionaryapproachestosolvetheflowshopschedulingproblem
bdutipo_str Repositorios
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