An ACO model for a non-stationary formulation of the single elevator problem
- Autores
- Molina, Silvia; Leguizamón, Mario Guillermo; Alba Torres, Enrique
- Año de publicación
- 2007
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- The Ant Colony Optimization (ACO) metaheuristic is a bio-inspired approach for hard combinatorial optimization problems for stationary and non-stationary environments. In the ACO metaheuristic, a colony of artificial ants cooperate for finding high quality solutions in a reasonable time. An interesting example of a non-stationary combinatorial optimization problem is the Multiple Elevators Problem (MEP) which consists in finding a sequence of movements for each elevator to perform in a building so that to minimize, for instance, the users waiting average time. Events like the arrival of one new user to the elevator queue or the fault of one elevator dynamically produce changes of state in this problem. A subclass of MEP is the the so called Single Elevator Problem (SEP). In this work, we propose the design of an ACO model for the SEP that can be implemented as an Ant Colony System (ACS). Keywords: Ant Colony Optimization, Single Elevator Problem, Non-stationary Problems, Ant Colony System design.
Facultad de Informática - Materia
-
Ciencias Informáticas
Ant Colony Optimization (ACO)
Single Elevator Problem (SEP) - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc/3.0/
- Repositorio
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/9527
Ver los metadatos del registro completo
| id |
SEDICI_daf531b3eb0849a8c6e319d424ffcb31 |
|---|---|
| oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/9527 |
| network_acronym_str |
SEDICI |
| repository_id_str |
1329 |
| network_name_str |
SEDICI (UNLP) |
| spelling |
An ACO model for a non-stationary formulation of the single elevator problemMolina, SilviaLeguizamón, Mario GuillermoAlba Torres, EnriqueCiencias InformáticasAnt Colony Optimization (ACO)Single Elevator Problem (SEP)The Ant Colony Optimization (ACO) metaheuristic is a bio-inspired approach for hard combinatorial optimization problems for stationary and non-stationary environments. In the ACO metaheuristic, a colony of artificial ants cooperate for finding high quality solutions in a reasonable time. An interesting example of a non-stationary combinatorial optimization problem is the Multiple Elevators Problem (MEP) which consists in finding a sequence of movements for each elevator to perform in a building so that to minimize, for instance, the users waiting average time. Events like the arrival of one new user to the elevator queue or the fault of one elevator dynamically produce changes of state in this problem. A subclass of MEP is the the so called Single Elevator Problem (SEP). In this work, we propose the design of an ACO model for the SEP that can be implemented as an Ant Colony System (ACS). Keywords: Ant Colony Optimization, Single Elevator Problem, Non-stationary Problems, Ant Colony System design.Facultad de Informática2007-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf41-51http://sedici.unlp.edu.ar/handle/10915/9527enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Mar07-8.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/3.0/Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:50:44Zoai:sedici.unlp.edu.ar:10915/9527Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:50:44.292SEDICI (UNLP) - Universidad Nacional de La Platafalse |
| dc.title.none.fl_str_mv |
An ACO model for a non-stationary formulation of the single elevator problem |
| title |
An ACO model for a non-stationary formulation of the single elevator problem |
| spellingShingle |
An ACO model for a non-stationary formulation of the single elevator problem Molina, Silvia Ciencias Informáticas Ant Colony Optimization (ACO) Single Elevator Problem (SEP) |
| title_short |
An ACO model for a non-stationary formulation of the single elevator problem |
| title_full |
An ACO model for a non-stationary formulation of the single elevator problem |
| title_fullStr |
An ACO model for a non-stationary formulation of the single elevator problem |
| title_full_unstemmed |
An ACO model for a non-stationary formulation of the single elevator problem |
| title_sort |
An ACO model for a non-stationary formulation of the single elevator problem |
| dc.creator.none.fl_str_mv |
Molina, Silvia Leguizamón, Mario Guillermo Alba Torres, Enrique |
| author |
Molina, Silvia |
| author_facet |
Molina, Silvia Leguizamón, Mario Guillermo Alba Torres, Enrique |
| author_role |
author |
| author2 |
Leguizamón, Mario Guillermo Alba Torres, Enrique |
| author2_role |
author author |
| dc.subject.none.fl_str_mv |
Ciencias Informáticas Ant Colony Optimization (ACO) Single Elevator Problem (SEP) |
| topic |
Ciencias Informáticas Ant Colony Optimization (ACO) Single Elevator Problem (SEP) |
| dc.description.none.fl_txt_mv |
The Ant Colony Optimization (ACO) metaheuristic is a bio-inspired approach for hard combinatorial optimization problems for stationary and non-stationary environments. In the ACO metaheuristic, a colony of artificial ants cooperate for finding high quality solutions in a reasonable time. An interesting example of a non-stationary combinatorial optimization problem is the Multiple Elevators Problem (MEP) which consists in finding a sequence of movements for each elevator to perform in a building so that to minimize, for instance, the users waiting average time. Events like the arrival of one new user to the elevator queue or the fault of one elevator dynamically produce changes of state in this problem. A subclass of MEP is the the so called Single Elevator Problem (SEP). In this work, we propose the design of an ACO model for the SEP that can be implemented as an Ant Colony System (ACS). Keywords: Ant Colony Optimization, Single Elevator Problem, Non-stationary Problems, Ant Colony System design. Facultad de Informática |
| description |
The Ant Colony Optimization (ACO) metaheuristic is a bio-inspired approach for hard combinatorial optimization problems for stationary and non-stationary environments. In the ACO metaheuristic, a colony of artificial ants cooperate for finding high quality solutions in a reasonable time. An interesting example of a non-stationary combinatorial optimization problem is the Multiple Elevators Problem (MEP) which consists in finding a sequence of movements for each elevator to perform in a building so that to minimize, for instance, the users waiting average time. Events like the arrival of one new user to the elevator queue or the fault of one elevator dynamically produce changes of state in this problem. A subclass of MEP is the the so called Single Elevator Problem (SEP). In this work, we propose the design of an ACO model for the SEP that can be implemented as an Ant Colony System (ACS). Keywords: Ant Colony Optimization, Single Elevator Problem, Non-stationary Problems, Ant Colony System design. |
| publishDate |
2007 |
| dc.date.none.fl_str_mv |
2007-04 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Articulo http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/9527 |
| url |
http://sedici.unlp.edu.ar/handle/10915/9527 |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Mar07-8.pdf info:eu-repo/semantics/altIdentifier/issn/1666-6038 |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc/3.0/ Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) |
| eu_rights_str_mv |
openAccess |
| rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc/3.0/ Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) |
| dc.format.none.fl_str_mv |
application/pdf 41-51 |
| dc.source.none.fl_str_mv |
reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
| reponame_str |
SEDICI (UNLP) |
| collection |
SEDICI (UNLP) |
| instname_str |
Universidad Nacional de La Plata |
| instacron_str |
UNLP |
| institution |
UNLP |
| repository.name.fl_str_mv |
SEDICI (UNLP) - Universidad Nacional de La Plata |
| repository.mail.fl_str_mv |
alira@sedici.unlp.edu.ar |
| _version_ |
1844615757947731968 |
| score |
13.070432 |