An ACO approach for the parallel machines scheduling problem
; Esquivel, Susana Cecilia ; Leguizamon, Mario Guillermo Otros responsables
Fecha
06/2010
Editorial
Sociedad Iberoamericana de Inteligencia Artificial
Revista
Inteligencia Artificial
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Institución organizadora
ISSN
1137-3601
eISSN
1988-3064
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Inglés
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Resumen
The parallel machines scheduling problem (PMSP) comprises the allocation of jobs on the resources of the systems, 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 four different specific heuristics in the solution construction process to solve unrestricted PMSP for the minimization of the Maximum Tardiness (Tmax) objective. 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.
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