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dc.date.accessioned 2012-09-28T17:08:36Z
dc.date.available 2012-09-28T17:08:36Z
dc.date.issued 2008
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/21771
dc.description.abstract The parallel machines scheduling problem (Pm) comprises the allocation of jobs on the system’s resources, i.e., a group of machines in parallel. The basic model consists of m identical machines and n jobs. The jobs are assigned according to resource availability following some allocation rule. In this work, we apply the Ant Colony Optimization (ACO) metaheuristic which includes in the construction solution process different specific heuristic to solve Pm for the minimization Maximum Tardiness (Tmax). We also present a comparison of previous results obtained by a simple genetic algorithm (GAs) and an evidence of an improved performance of the ACO metaheuristic on this particular scheduling problem. en
dc.language en es
dc.subject Parallel es
dc.subject Ant Colony Optimization (ACO) en
dc.subject Scheduling es
dc.subject Optimization es
dc.subject Heuristic methods es
dc.title An ACO approach for the Parallel Machines Scheduling Problem en
dc.type Objeto de conferencia es
sedici.creator.person Gatica, Claudia R. es
sedici.creator.person Esquivel, Susana Cecilia es
sedici.creator.person Leguizamón, Guillermo es
sedici.description.note Workshop de Agentes y Sistemas Inteligentes (WASI) es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2008-10
sedici.relation.event XIV Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)