Abstract
Attaining optimal results in real-life scheduling is hindered by a number of problems. One such problem is dynamics of manufacturing environments with breaking-down resources and hot orders coming during the schedule execution. A traditional approach to react to unexpected events occurring on the shop floor is generating a new schedule from scratch. Complete rescheduling, however, may require excessive computation time. Moreover, the recovered schedule may deviate a lot from the ongoing schedule. Some works have focused on tackling these shortcomings, but none of the existing approaches tries to substitute jobs that cannot be executed with a set of alternative jobs. This paper describes the scheduling model suitable for dealing with unforeseen events using the possibility of alternative processes and proposes an efficient heuristic-based approach to recover an ongoing schedule from a resource failure.
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Acknowledgments
This research is partially supported by the Charles University in Prague, project GA UK No. 158216, by SVV project number 260 333, and by the Czech Science Foundation under the project P103-15-19877S.
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Barták, R., Vlk, M. (2017). Hierarchical Task Model for Resource Failure Recovery in Production Scheduling. In: Sidorov, G., Herrera-Alcántara, O. (eds) Advances in Computational Intelligence. MICAI 2016. Lecture Notes in Computer Science(), vol 10061. Springer, Cham. https://doi.org/10.1007/978-3-319-62434-1_30
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