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Mostrar registro sencillo 2008-05-21T19:26:21Z 2008-05-21T03:00:00Z 2007-04
dc.description.abstract 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. en
dc.format.extent p. 41-51 es
dc.language en es
dc.title An ACO model for a non-stationary formulation of the single elevator problem en
dc.type Articulo es
sedici.identifier.uri es
sedici.identifier.issn 1666-6038 es
sedici.creator.person Molina, Silvia es
sedici.creator.person Leguizamón, Mario Guillermo es
sedici.creator.person Alba Torres, Enrique es
sedici.subject.materias Ciencias Informáticas es
sedici.subject.other Ant Colony Optimization (ACO) en
sedici.subject.other Single Elevator Problem (SEP) en
sedici.description.fulltext true es Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
sedici.description.peerReview peer-review es
sedici2003.identifier ARG-UNLP-ART-0000000575 es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 7, no. 1 es

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Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)