Abstract
In real-world manufacturing systems, schedules are often confronted with uncertainty factors such as random machine breakdown, random process time, random job arrivals or job cancellations. A large number of impromptu disruptions frequently affect the scheduled operations and invalidate the original schedule. There is still the need for rescheduling methods that can work effectively in disruption management. In this work, an algorithm for rescheduling the affected operations in a flexible job shop is presented and its performance, with respect to measures of efficiency and stability, is compared with the Right Shift Rescheduling technique. The proposed method is tested on different benchmark scheduling problems with various disruption scenarios. Experimental results show that the proposed rescheduling method improves the efficiency and stability when compared to Right Shift Rescheduling method.
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Acknowledgements
The research work presented in this paper comes from the ELSAT2020 project of CPER sponsored by the French Ministry of Sciences, the Haut de France region and the FEDER.
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Nouiri, M., Bekrar, A., Jemai, A., Ammari, A.C., Niar, S. (2018). A New Rescheduling Heuristic for Flexible Job Shop Problem with Machine Disruption. In: Borangiu, T., Trentesaux, D., Thomas, A., Cardin, O. (eds) Service Orientation in Holonic and Multi-Agent Manufacturing. Studies in Computational Intelligence, vol 762. Springer, Cham. https://doi.org/10.1007/978-3-319-73751-5_35
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DOI: https://doi.org/10.1007/978-3-319-73751-5_35
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