Empirical improvements of a dynamic scheduling engine in an industrial environment

Mohanna, Mahmoud et Chaabane, Amin. 2016. « Empirical improvements of a dynamic scheduling engine in an industrial environment ». In 11th International Conference on Modeling, Optimization and Simulation - MOSIM'16: Innovation in Technology for performant Systems (Montreal, QC, Canada, Aug. 22-24, 2016)

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Résumé

This paper introduces the results of a series of empirical improvements performed on a basic algorithm addressing the Flow Shop Scheduling Problem in an industrial environment. Metaheuristic methods are followed to enhance the time and the quality of the initial solution produced by the scheduling engine of an industrial platform in order to obtain a rather acceptable initial schedule. Thereafter, several boosts have been achieved in order to accelerate the convergence towards an optimum solution besides the reduction of processing time and memory allocation. Further research work is required to improve resource assignation by making it more efficient and reasonable and to optimize memory allocation so that the current scheduling engine becomes more scalable and updatable.

Type de document:	Compte rendu de conférence
Professeur:	Professeur Chaabane, Amin
Affiliation:	Génie de la production automatisée
Date de dépôt:	12 janv. 2017 16:22
Dernière modification:	12 janv. 2017 21:02
URI:	https://espace2.etsmtl.ca/id/eprint/14284

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