A showcase of ÉTS researchers’ publications and other contributions

Empirical improvements of a dynamic scheduling engine in an industrial environment


Downloads per month over past year

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)

[thumbnail of Empirical-improvements-of-a-dynamic-scheduling-engine-in-an-industrial-environment.pdf]

Download (788kB) | Preview


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.

Item Type: Conference proceeding
Chaabane, Amin
Affiliation: Génie de la production automatisée
Date Deposited: 12 Jan 2017 16:22
Last Modified: 12 Jan 2017 21:02

Actions (login required)

View Item View Item