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
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/9527

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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:UNLP2025-09-03T10:23:34Zoai: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:13292025-09-03 10:23:34.627SEDICI (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
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dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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