An ACO approach for the Parallel Machines Scheduling Problem

• Autores: Claudia Ruth Gatica, Susana Esquivel, Guillermo Leguizamón
• Localización: Inteligencia artificial: Revista Iberoamericana de Inteligencia Artificial, ISSN-e 1988-3064, ISSN 1137-3601, Vol. 14, Nº. 46, 2010, págs. 84-95
• Idioma: 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.