Artículo

An ACO approach for the parallel machines scheduling problem

Gatica, Claudia Ruth Icon; Esquivel, Susana Cecilia ; Leguizamon, Mario Guillermo

Otros responsables

Fecha

06/2010

Editorial

Sociedad Iberoamericana de Inteligencia Artificial

Revista

Inteligencia Artificial

Título del libro

Nombre del evento

Fecha del evento

Institución organizadora

ISSN

1137-3601

eISSN

1988-3064

ISBN

Idioma

Inglés

Tipo del evento

Clasificación temática

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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