Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/82984
Título
GRASP algorithms for the unrelated parallel machines scheduling problem with additional resources during processing and setups
Año del Documento
2022
Editorial
Taylor & Francis
Descripción
Producción Científica
Documento Fuente
International Journal of Production Research, Sep 2022, 61(17), 6013-6029
Résumé
This paper addresses an unrelated parallel machines scheduling problem with the need of additional resources during the processing of the jobs, as well as during the setups that machines need between the processing of any two jobs. This problem is highly complex, and therefore in this paper we propose several constructive heuristics to solve it. To improve the performance of these heuristics, we propose several variations, including randomisation with different probability distributions and a local search phase, having this way GRASP algorithms. The results of extensive experiments over randomly generated instances show several findings on the different parameters that characterise our constructive algorithms. In particular, we highlight the fact that non-uniform probability distributions might be advisable for choosing elements of a restricted candidate list in GRASP algorithms.
Palabras Clave
Parallel machines, scheduling, sequence dependent setup times, additional resources, metaheuristics, GRASP
ISSN
0020-7543
Revisión por pares
SI
Patrocinador
Este trabajo forma parte del proyecto de investigación: AT21_00032 Optimización Aplicada al Tejido Productivo Andaluz, y del proyecto NUevos REtos en SEcuenciación (No. AICO/2020/049) de la generalitat valenciana
Idioma
eng
Tipo de versión
info:eu-repo/semantics/draft
Derechos
openAccess
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